### 1. notes , from the report of the court of auditor’s (the ‘court’s report’) on the annual accounts of the joint undertaking for the financial year 2021 , that the annual accounts present fairly , in all material respects , the financial position of the joint undertaking on 31 december 2021 , the results of its operations , its cash flows , and the changes in net assets for the year then ended , in accordance with its financial regulation and with accounting rules adopted by the commission’s accounting officer; notes , furthermore , from the court’s report that the underlying transactions to the accounts are , in all material respects , legal and regular; ### 1. welcomes that the annual accounts present fairly , in all material respects , the financial position of the joint undertaking on 31 december 2021 , the results of its operations , its cash flows , and the changes in net assets for the year then ended , in accordance with its financial regulation and with accounting rules adopted by the commission’s accounting officer; highlights furthermore that the underlying transactions to the accounts are , in all material respects , legal and regular;


### 4. notes , from the report on the budgetary and financial management 2021 , the 2021 eu-rail budget does not include any revenue or commitment/payment appropriations in relation with eu-rail resources coming from horizon europe or its private members; notes that it consists only of appropriations related to shift2rail and shift2rail members; ### 4. underlines that the 2021 eu-rail budget does not include any revenue or commitment/payment appropriations in relation with eu-rail resources coming from horizon europe or its private members and that it consists only of appropriations related to shift2rail and shift2rail members;


### 6. notes that , at the year-end 2021 , the undertaking had implemented 100% of its commitment appropriations made available in its active budget , which include staff and administrative expenditure; notes that the payment appropriations were implemented up to 85% of the active funds; notes that the implementation when compared to the full joint undertaking budget , including unused appropriations not required in current year , was 100% in commitment and 63% in payment appropriations; ### 6. welcomes that , at the year-end 2021 , the undertaking had implemented 100% of its commitment appropriations made available in its active budget , which include staff and administrative expenditure and that the payment appropriations were implemented up to 85% of the active funds; notes that the implementation when compared to the full joint undertaking budget , including unused appropriations not required in current year , was 100% in commitment and 63% in payment appropriations;


### 9. notes , from the court’s report , that the joint undertaking implemented 100% of its commitment budget available for horizon 2020 projects; notes that the implementation rate for the joint undertaking’s 2021 operational payment budget available , including operational unused and reallocated appropriations , fell to 61% (2020: 76%); notes that this situation was mainly caused by the poor quality of the beneficiaries’ technical reports and/or the need to request from the beneficiaries , additional evidence confirming the achievement of project results; notes , moreover , that most of the joint undertaking’s payment are lump-sumps paid for project work packages that have been properly implemented by multiple beneficiaries; notes , therefore , that the delay of a single beneficiary affects the payment of the whole lump-sum amount related to the work package; ### 9. highlights that the joint undertaking implemented 100% of its commitment budget available for horizon 2020 projects; notes that the implementation rate for the joint undertaking’s 2021 operational payment budget available , including operational unused and reallocated appropriations , fell to 61% (2020: 76%); is aware that this situation was mainly caused by the poor quality of the beneficiaries’ technical reports and/or the need to request from the beneficiaries , additional evidence confirming the achievement of project results; calls on the joint undertaking to explore any additional means of facilitating the reporting rules for achievements of project results in order to avoid delays in the future; notes , moreover , that most of the joint undertaking’s payment are lump-sumps paid for project work packages that have been properly implemented by multiple beneficiaries; notes , therefore , that the delay of a single beneficiary affects the payment of the whole lump-sum amount related to the work package;


### 11. notes that , during 2021 , the joint undertaking has further progressed in delivering the shift2rail programme , although operational activities have been affected by the covid-19 pandemic , further delaying the programme outputs of about additional 6 months compared to 2020 delays , in particular due to the increased number of demonstration activities on-site that were active in 2021; notes that the internal control system in place has ensured effective and efficient sound financial management; ### 11. welcomes that , during 2021 , the joint undertaking has further progressed in delivering the shift2rail programme , although operational activities have been affected by the covid-19 pandemic , further delaying the programme outputs of about additional 6 months compared to 2020 delays , in particular due to the increased number of demonstration activities on-site that were active in 2021; is pleased that the internal control system in place has ensured effective and efficient sound financial management;


### 13. notes that , by the end of 2021 , the shift2rail programme reached pivotal milestones in term of programme implementation with almost all shift2rail resources being committed for the programme activities and all planned innovative programme/cross cutting activities related activities were running in granted projects; notes that , on average , almost 75% of the programme has been realised in view of reaching the technology readiness level 6/72 operational demonstrations planned for conclusion during 2023; notes that , in total , it is estimated that the total value of the activities performed in 2021 amounts to eur 123.5 million , of which eur 113.6 million delivered by the members other than the european union; ### 13. highlights that , by the end of 2021 , the shift2rail programme reached pivotal milestones in term of programme implementation with almost all shift2rail resources being committed for the programme activities and all planned innovative programme/cross cutting activities related activities were running in granted projects; appreciates that , on average , almost 75% of the programme has been realised in view of reaching the technology readiness level 6/72 operational demonstrations planned for conclusion during 2023; notes that , in total , it is estimated that the total value of the activities performed in 2021 amounts to eur 123.5 million , of which eur 113.6 million delivered by the members other than the european union;


### 18. notes that , in 2021 , the staff turnover continued to be high with some staff members and one sne leaving the joint undertaking; notes that this was attributable , besides other aspects , to the fact that other union joint undertakings are in the position to offer temporary agent posts (ta) instead of contractual agent posts (ca); ### 18. regrets that , in 2021 , the staff turnover continued to be high with some staff members and one sne leaving the joint undertaking; notes that this was attributable , besides other aspects , to the fact that other union joint undertakings are in the position to offer temporary agent posts (ta) instead of contractual agent posts (ca);


### 19. notes that , as it was the case already in 2020 , the joint undertaking continued also in 2021 to follow the ec approach in response to the covid-19 pandemic by implementing special measures designed to protect staff; notes that , in particular , this was ensured by applying teleworking arrangements , and , when working onsite , by decreasing physical contacts between colleagues and utilising protective measures; notes , in addition that the joint undertaking strived to tackle the negative effects of the pandemic on the staff’s mental health by introducing already in 2020 a wellbeing programme; ### 19. welcomes that , as it was the case already in 2020 , the joint undertaking continued also in 2021 to follow the ec approach in response to the covid-19 pandemic by implementing special measures designed to protect staff; notes that , in particular , this was ensured by applying teleworking arrangements , and , when working onsite , by decreasing physical contacts between colleagues and utilising protective measures; is pleased that the joint undertaking strived to tackle the negative effects of the pandemic on the staff’s mental health by introducing already in 2020 a wellbeing programme;


### 21. notes that , following the court’s observations , that the eu-rail agrees to pay its employer’s pension contributions in line with the calculation to be provided by the commission’s services , once de-jure aspects are ascertained; ### 21. welcomes that , following the court’s observations , that the eu-rail agrees to pay its employer’s pension contributions in line with the calculation to be provided by the commission’s services , once de-jure aspects are ascertained; calls on the joint undertaking not to wait for the final calculation of outstanding contributions , but to consider this obligation when planning its future budget e.g. through a corresponding accrual for pension contributions;


### 25. notes that , in 2020 , the joint undertaking adopted a revised internal control framework; notes that a first annual self-assessment of the revised internal control framework was performed in q1 2021 in order to evaluate the compliance and effectiveness of internal controls , looking back to 2020 , as well as reflecting the current situation in internal control activities existing at that time; ### 25. highlights that , in 2020 , the joint undertaking adopted a revised internal control framework and that a first annual self-assessment of the revised internal control framework was performed in q1 2021 in order to evaluate the compliance and effectiveness of internal controls , looking back to 2020 , as well as reflecting the current situation in internal control activities existing at that time;


### 29. notes that , as for the treatment of potential conflicts of interests , and to implement the requirements following from its constituent act with regard to this matter , the joint undertaking has adopted the respective rules by means of its internal legal framework in relation to its members , staff , as well as the members of its governing board; notes that the annual declarations of interests of the latter are publicly available in the joint undertaking official website. ### 29. underlines that , as for the treatment of potential conflicts of interests , and to implement the requirements following from its constituent act with regard to this matter , the joint undertaking has adopted the respective rules by means of its internal legal framework in relation to its members , staff , as well as the members of its governing board and that the annual declarations of interests of the latter are publicly available in the joint undertaking official website.


### (1) the purpose of this regulation is to improve the functioning of the internal market by laying down a uniform legal framework in particular for the development , marketing and use of artificial intelligence in conformity with union values. this regulation pursues a number of overriding reasons of public interest , such as a high level of protection of health , safety and fundamental rights , and it ensures the free movement of ai-based goods and services cross-border , thus preventing member states from imposing restrictions on the development , marketing and use of ai systems , unless explicitly authorised by this regulation. ### (1) the purpose of this regulation is to improve the functioning of the internal market by laying down a uniform legal framework in particular for the development , marketing and use of artificial intelligence in conformity with union values without hampering innovation , deployment and uptake of artificial intelligence and the beneficial contributions the technology can bring to individuals , businesses as well as society and economy at large. this regulation pursues a number of overriding reasons of public interest , such as a high level of protection of health , safety and fundamental rights , and it ensures the free movement of ai-based goods and services cross-border , thus preventing member states from imposing restrictions on the development , marketing and use of ai systems , unless explicitly authorised by this regulation.


### (1) the purpose of this regulation is to improve the functioning of the internal market by laying down a uniform legal framework in particular for the development , marketing and use of artificial intelligence in conformity with union values. this regulation pursues a number of overriding reasons of public interest , such as a high level of protection of health , safety and fundamental rights , and it ensures the free movement of ai-based goods and services cross-border , thus preventing member states from imposing restrictions on the development , marketing and use of ai systems , unless explicitly authorised by this regulation. ### (1) the purpose of this regulation is to improve the functioning of the internal market by laying down a harmonised , balanced and uniform legal framework in particular for the development , marketing and use of artificial intelligence in conformity with the union’s fundamental values , principles , objectives and rights. this regulation pursues a number of overriding reasons of public interest , such as a high level of protection of health , safety and fundamental rights , and it ensures the free movement of ai-based goods and services cross-border , thus preventing member states from imposing restrictions on the development , marketing and use of ai systems , unless explicitly authorised by this regulation.


### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. by laying down those rules , this regulation supports the objective of the union of being a global leader in the development of secure , trustworthy and ethical artificial intelligence , as stated by the european council33 , and it ensures the protection of ethical principles , as specifically requested by the european parliament34 . ### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. by laying down those rules , this regulation supports the objective of the union of being a global leader in the development of secure , trustworthy and ethical artificial intelligence , as stated by the european council33 , and it ensures the protection of ethical principles , as specifically requested by the european parliament34 with a human-centric approach and in compliance with freedom of expression , freedom of speech , media freedom , pluralism and cultural diversity.


### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. by laying down those rules , this regulation supports the objective of the union of being a global leader in the development of secure , trustworthy and ethical artificial intelligence , as stated by the european council33 , and it ensures the protection of ethical principles , as specifically requested by the european parliament34 . ### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. these rules should be supportive to new innovative solutions and robust in protecting fundamental rights of all the actors. by laying down those rules , this regulation supports the objective of the union of being a global leader in the development of secure , trustworthy and ethical artificial intelligence , as stated by the european council , and it ensures the protection of ethical principles , as specifically requested. one of the fundamental principles of this legislative framework is that there is no doubt between the protection of fundamental rights or the support of innovation , since this regulation provides rules that adequately address both of mentioned priorities.


### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. by laying down those rules , this regulation supports the objective of the union of being a global leader in the development of secure , trustworthy and ethical artificial intelligence , as stated by the european council33 , and it ensures the protection of ethical principles , as specifically requested by the european parliament34 . ### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. furthermore , clear rules supporting the application and design of ai systems should be laid down , thus enabling a european ecosystem of public and private actors creating ai systems in line with european values. by laying down those rules , this regulation supports the objective of the union of being a global leader in the development of secure , trustworthy and ethical artificial intelligence , as stated by the european council33 , and it ensures the protection of ethical principles , as specifically requested by the european parliament34.


### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. by laying down those rules , this regulation supports the objective of the union of being a global leader in the development of secure , trustworthy and ethical artificial intelligence , as stated by the european council33 , and it ensures the protection of ethical principles , as specifically requested by the european parliament34 . ### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. by laying down those rules , this regulation supports the objective of the union of promoting the "ai made in europe" and being a global leader in the development of secure , trustworthy and ethical artificial intelligence , as stated by the european council33 , and it ensures the protection of ethical principles , as specifically requested by the european parliament34 .


### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. by laying down those rules , this regulation supports the objective of the union of being a global leader in the development of secure , trustworthy and ethical artificial intelligence , as stated by the european council33 , and it ensures the protection of ethical principles , as specifically requested by the european parliament34 . ### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public and private interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. by laying down those rules , this regulation supports the objective of the union of being a global leader in the development of secure , trustworthy and ethical artificial intelligence , as stated by the european council33 , and it ensures the protection of ethical principles , as specifically requested by the european parliament34 .


### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. by laying down those rules , this regulation supports the objective of the union of being a global leader in the development of secure , trustworthy and ethical artificial intelligence , as stated by the european council33 , and it ensures the protection of ethical principles , as specifically requested by the european parliament34 . ### (5) a union legal framework laying down harmonised rules on artificial intelligence is therefore needed to foster the development , use and uptake of artificial intelligence in the internal market that at the same time meets a high level of protection of public interests , such as health and safety and the protection of fundamental rights , as recognised and protected by union law. to achieve that objective , rules regulating the placing on the market and putting into service of certain ai systems should be laid down , thus ensuring the smooth functioning of the internal market and allowing those systems to benefit from the principle of free movement of goods and services. by laying down those rules , this regulation supports the objective of the union of being a global leader in the development of secure , non-biased trustworthy and ethical artificial intelligence , as stated by the european council33 , and it ensures the protection of ethical principles , as specifically requested by the european parliament34 .


### (6) the notion of ai system should be clearly defined to ensure legal certainty , while providing the flexibility to accommodate future technological developments. the definition should be based on the key functional characteristics of the software , in particular the ability , for a given set of human-defined objectives , to generate outputs such as content , predictions , recommendations , or decisions which influence the environment with which the system interacts , be it in a physical or digital dimension. ai systems can be designed to operate with varying levels of autonomy and be used on a stand-alone basis or as a component of a product , irrespective of whether the system is physically integrated into the product (embedded) or serve the functionality of the product without being integrated therein (non-embedded). the definition of ai system should be complemented by a list of specific techniques and approaches used for its development , which should be kept up-to–date in the light of market and technological developments through the adoption of delegated acts by the commission to amend that list. ### (6) the notion of ai system should be clearly defined to ensure legal and commercial certainty , and be in line with internationally accepted definitions , while providing the flexibility to accommodate future technological developments. the commission should pursue dialogue with key international organisations so as to ensure that there is alignment and common understanding of precisely what ai systems entail. the definition should be based on the key functional characteristics of the software , in particular the ability , for a given set of human-defined objectives , to generate outputs such as content , predictions , recommendations , or decisions which influence the environment with which the system interacts , be it in a physical or digital dimension. ai systems can be designed to operate with varying levels of autonomy and be used on a stand-alone basis or as a component of a product , irrespective of whether the system is physically integrated into the product (embedded) or serve the functionality of the product without being integrated therein (non-embedded). the definition of ai system should be complemented by a list of specific techniques and approaches used for its development , which should be kept up-to–date in the light of market and technological developments through the adoption of delegated acts by the commission to amend that list.


### (6) the notion of ai system should be clearly defined to ensure legal certainty , while providing the flexibility to accommodate future technological developments. the definition should be based on the key functional characteristics of the software , in particular the ability , for a given set of human-defined objectives , to generate outputs such as content , predictions , recommendations , or decisions which influence the environment with which the system interacts , be it in a physical or digital dimension. ai systems can be designed to operate with varying levels of autonomy and be used on a stand-alone basis or as a component of a product , irrespective of whether the system is physically integrated into the product (embedded) or serve the functionality of the product without being integrated therein (non-embedded). the definition of ai system should be complemented by a list of specific techniques and approaches used for its development , which should be kept up-to–date in the light of market and technological developments through the adoption of delegated acts by the commission to amend that list. ### (6) the notion of ai system should be clearly defined to ensure legal certainty , while providing the flexibility to accommodate future technological developments. this definition should be in line with definitions that have found international acceptance. moreover , it should be based on the key functional characteristics of artificial intelligence distinguishing it from more classic software systems and modelling approaches such as logistic regression and other techniques that are similarly transparent , explainable and interpretable. for the purposes of this regulation , the definition should be based on the key functional characteristics of the ai system , in particular its ability , for a given set of human-defined objectives , to make predictions , recommendations , or decisions that influence real or virtual environments , whereby it uses machine and/or human-based data and inputs to (i) perceive real and/or virtual environments; (ii) abstract these perceptions into models through analysis in an automated manner (e.g. with machine learning) , or manually; and (iii) use model inference to formulate options for outcomes. ai systems are designed to operate with varying levels of autonomy and can be used on a stand-alone software system , integrated into a physical product (embedded) , used to serve the functionality of a physical product without being integrated therein (non-embedded) or used as a subsystem of a software/physical/hybrid system of systems. if an ai system is used as a subsystem of a system of systems , then all parts including their interfaces to other parts of the system of systems that would be obsolete if the ai functionality were turned off or removed are essential parts of the ai system thus fall directly under this regulation. any parts of the system of systems to which this does not hold true are not covered by this regulation and the obligations listed in this regulation do not apply to them. this is to ensure that the integration of ai systems into existing systems is not blocked by this regulation.


### (6) the notion of ai system should be clearly defined to ensure legal certainty , while providing the flexibility to accommodate future technological developments. the definition should be based on the key functional characteristics of the software , in particular the ability , for a given set of human-defined objectives , to generate outputs such as content , predictions , recommendations , or decisions which influence the environment with which the system interacts , be it in a physical or digital dimension. ai systems can be designed to operate with varying levels of autonomy and be used on a stand-alone basis or as a component of a product , irrespective of whether the system is physically integrated into the product (embedded) or serve the functionality of the product without being integrated therein (non-embedded). the definition of ai system should be complemented by a list of specific techniques and approaches used for its development , which should be kept up-to–date in the light of market and technological developments through the adoption of delegated acts by the commission to amend that list. ### (6) the notion of ai system should be clearly defined to ensure legal certainty , while providing the flexibility to accommodate existing harmless applications and future technological developments. the definition should be based on the key functional characteristics of the software , in particular the ability , for a given set of human-defined objectives , to generate outputs such as content , predictions , recommendations , or decisions which influence the environment with which the system interacts , be it in a physical or digital dimension. ai systems can be designed to operate with varying levels of autonomy and be used on a stand-alone basis or as a component of a product , irrespective of whether the system is physically integrated into the product (embedded) or serve the functionality of the product without being integrated therein (non-embedded). the definition of ai system should be complemented by a list of specific techniques and approaches used for its development , which should be kept up-to–date in the light of market and technological developments through the adoption of delegated acts by the commission to amend that list.


### (6) the notion of ai system should be clearly defined to ensure legal certainty , while providing the flexibility to accommodate future technological developments. the definition should be based on the key functional characteristics of the software , in particular the ability , for a given set of human-defined objectives , to generate outputs such as content , predictions , recommendations , or decisions which influence the environment with which the system interacts , be it in a physical or digital dimension. ai systems can be designed to operate with varying levels of autonomy and be used on a stand-alone basis or as a component of a product , irrespective of whether the system is physically integrated into the product (embedded) or serve the functionality of the product without being integrated therein (non-embedded). the definition of ai system should be complemented by a list of specific techniques and approaches used for its development , which should be kept up-to–date in the light of market and technological developments through the adoption of delegated acts by the commission to amend that list. ### (6) the notion of ai system should be clearly defined to ensure legal certainty , while providing the flexibility to accommodate future technological developments. the definition should be aligned with internationally accepted approach. ai systems can be designed to operate with varying levels of autonomy and be used on a stand-alone basis or as a component of a product , irrespective of whether the system is physically integrated into the product (embedded) or serve the functionality of the product without being integrated therein (non-embedded). the definition of ai system should be complemented by a list of specific techniques and approaches used for its development , which should be kept up-to–date in the light of market and technological developments through the adoption of delegated acts by the commission to amend that list. the commission should engage in dialogue with key international organizations , so that the common international standards could be achieved to the highest possible extent.


### (6) the notion of ai system should be clearly defined to ensure legal certainty , while providing the flexibility to accommodate future technological developments. the definition should be based on the key functional characteristics of the software , in particular the ability , for a given set of human-defined objectives , to generate outputs such as content , predictions , recommendations , or decisions which influence the environment with which the system interacts , be it in a physical or digital dimension. ai systems can be designed to operate with varying levels of autonomy and be used on a stand-alone basis or as a component of a product , irrespective of whether the system is physically integrated into the product (embedded) or serve the functionality of the product without being integrated therein (non-embedded). the definition of ai system should be complemented by a list of specific techniques and approaches used for its development , which should be kept up-to–date in the light of market and technological developments through the adoption of delegated acts by the commission to amend that list. ### (6) the notion of ai system should be clearly defined to ensure legal certainty , while providing the flexibility to accommodate future technological developments , such as neurotechnology , which may put mental privacy at risk and require legislative proposals to protect neurodata and other sensitive health data. the definition should be based on the key functional characteristics of the software , in particular the ability , for a given set of human-defined objectives , to generate outputs such as content , predictions , recommendations , or decisions which influence the environment with which the system interacts , be it in a physical or digital dimension. ai systems can be designed to operate with varying levels of autonomy and be used on a stand-alone basis or as a component of a product , irrespective of whether the system is physically integrated into the product (embedded) or serve the functionality of the product without being integrated therein (non-embedded). the definition of ai system should be complemented by a list of specific techniques and approaches used for its development , which should be kept up-to–date in the light of market and technological developments through the adoption of delegated acts by the commission to amend that list.


### (18) the use of ai systems for ‘real-time’ remote biometric identification of natural persons in publicly accessible spaces for the purpose of law enforcement is considered particularly intrusive in the rights and freedoms of the concerned persons , to the extent that it may affect the private life of a large part of the population , evoke a feeling of constant surveillance and indirectly dissuade the exercise of the freedom of assembly and other fundamental rights. in addition , the immediacy of the impact and the limited opportunities for further checks or corrections in relation to the use of such systems operating in ‘real-time’ carry heightened risks for the rights and freedoms of the persons that are concerned by law enforcement activities. ### deleted


### (19) the use of those systems for the purpose of law enforcement should therefore be prohibited , except in three exhaustively listed and narrowly defined situations , where the use is strictly necessary to achieve a substantial public interest , the importance of which outweighs the risks. those situations involve the search for potential victims of crime , including missing children; certain threats to the life or physical safety of natural persons or of a terrorist attack; and the detection , localisation , identification or prosecution of perpetrators or suspects of the criminal offences referred to in council framework decision 2002/584/jha38 if those criminal offences are punishable in the member state concerned by a custodial sentence or a detention order for a maximum period of at least three years and as they are defined in the law of that member state. such threshold for the custodial sentence or detention order in accordance with national law contributes to ensure that the offence should be serious enough to potentially justify the use of ‘real-time’ remote biometric identification systems. moreover , of the 32 criminal offences listed in the council framework decision 2002/584/jha , some are in practice likely to be more relevant than others , in that the recourse to ‘real-time’ remote biometric identification will foreseeably be necessary and proportionate to highly varying degrees for the practical pursuit of the detection , localisation , identification or prosecution of a perpetrator or suspect of the different criminal offences listed and having regard to the likely differences in the seriousness , probability and scale of the harm or possible negative consequences. ### deleted


### (20) in order to ensure that those systems are used in a responsible and proportionate manner , it is also important to establish that , in each of those three exhaustively listed and narrowly defined situations , certain elements should be taken into account , in particular as regards the nature of the situation giving rise to the request and the consequences of the use for the rights and freedoms of all persons concerned and the safeguards and conditions provided for with the use. in addition , the use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for the purpose of law enforcement should be subject to appropriate limits in time and space , having regard in particular to the evidence or indications regarding the threats , the victims or perpetrator. the reference database of persons should be appropriate for each use case in each of the three situations mentioned above. ### deleted


### (21) each use of a ‘real-time’ remote biometric identification system in publicly accessible spaces for the purpose of law enforcement should be subject to an express and specific authorisation by a judicial authority or by an independent administrative authority of a member state. such authorisation should in principle be obtained prior to the use , except in duly justified situations of urgency , that is , situations where the need to use the systems in question is such as to make it effectively and objectively impossible to obtain an authorisation before commencing the use. in such situations of urgency , the use should be restricted to the absolute minimum necessary and be subject to appropriate safeguards and conditions , as determined in national law and specified in the context of each individual urgent use case by the law enforcement authority itself. in addition , the law enforcement authority should in such situations seek to obtain an authorisation as soon as possible , whilst providing the reasons for not having been able to request it earlier. ### (21) use of a ‘real-time’ remote biometric identification system in publicly accessible spaces for the purpose of law enforcement should be subject to authorisation by a judicial authority or by an independent administrative authority of a member state. the use should be subject to appropriate safeguards and conditions , as determined in national law and specified in the context of each case by the law enforcement authority itself.


### (21) each use of a ‘real-time’ remote biometric identification system in publicly accessible spaces for the purpose of law enforcement should be subject to an express and specific authorisation by a judicial authority or by an independent administrative authority of a member state. such authorisation should in principle be obtained prior to the use , except in duly justified situations of urgency , that is , situations where the need to use the systems in question is such as to make it effectively and objectively impossible to obtain an authorisation before commencing the use. in such situations of urgency , the use should be restricted to the absolute minimum necessary and be subject to appropriate safeguards and conditions , as determined in national law and specified in the context of each individual urgent use case by the law enforcement authority itself. in addition , the law enforcement authority should in such situations seek to obtain an authorisation as soon as possible , whilst providing the reasons for not having been able to request it earlier. ### (21) each use of a ‘real-time’ remote biometric identification system in publicly accessible spaces for the purpose of law enforcement should be subject to an express , specific and , in principle , prior authorisation by a judicial authority or by a competent independent administrative authority of a member state. such authorisation should in principle be obtained prior to the use , except in duly justified situations of demonstrable urgency , that is , situations where the need to use the systems in question is such as to make it effectively and objectively impossible to obtain an authorisation before commencing the use. in such situations of urgency , the use should be proportionate , be restricted to the absolute minimum necessary and be subject to appropriate safeguards and conditions , as determined in national law and specified in the context of each individual urgent use case by the competent law enforcement authority itself. in addition , the competent law enforcement authority should in such situations seek to obtain an authorisation as soon as possible , whilst providing the reasons for not having been able to request it earlier and the grounds for its use.


### (22) furthermore , it is appropriate to provide , within the exhaustive framework set by this regulation that such use in the territory of a member state in accordance with this regulation should only be possible where and in as far as the member state in question has decided to expressly provide for the possibility to authorise such use in its detailed rules of national law. consequently , member states remain free under this regulation not to provide for such a possibility at all or to only provide for such a possibility in respect of some of the objectives capable of justifying authorised use identified in this regulation. ### (22) furthermore , it is appropriate to provide that such use in the territory of a member state in accordance with this regulation should only be possible where and in as far as the member state in question has decided to expressly provide for the possibility to authorise such use in its detailed rules of national law. consequently , member states remain free under this regulation not to provide for such a possibility at all or to only provide for such a possibility.


### (23) the use of ai systems for ‘real-time’ remote biometric identification of natural persons in publicly accessible spaces for the purpose of law enforcement necessarily involves the processing of biometric data. the rules of this regulation that prohibit , subject to certain exceptions , such use , which are based on article 16 tfeu , should apply as lex specialis in respect of the rules on the processing of biometric data contained in article 10 of directive (eu) 2016/680 , thus regulating such use and the processing of biometric data involved in an exhaustive manner. therefore , such use and processing should only be possible in as far as it is compatible with the framework set by this regulation , without there being scope , outside that framework , for the competent authorities , where they act for purpose of law enforcement , to use such systems and process such data in connection thereto on the grounds listed in article 10 of directive (eu) 2016/680. in this context , this regulation is not intended to provide the legal basis for the processing of personal data under article 8 of directive 2016/680. however , the use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for purposes other than law enforcement , including by competent authorities , should not be covered by the specific framework regarding such use for the purpose of law enforcement set by this regulation. such use for purposes other than law enforcement should therefore not be subject to the requirement of an authorisation under this regulation and the applicable detailed rules of national law that may give effect to it. ### (23) the use of ai systems for ‘real-time’ remote biometric identification of natural persons in publicly accessible spaces for the purpose of law enforcement necessarily involves the processing of biometric data. the rules of this regulation , which are based on article 16 tfeu , should apply as lex specialis in respect of the rules on the processing of biometric data contained in article 10 of directive (eu) 2016/680. such use and processing should only be possible in as far as it is compatible with the framework set by this regulation , without there being scope , outside that framework , for the competent authorities , where they act for purpose of law enforcement , to use such systems and process such data in connection thereto on the grounds listed in article 10 of directive (eu) 2016/680. in this context , this regulation is not intended to provide the legal basis for the processing of personal data under article 8 of directive 2016/680. however , the use of ‘real-time’ remote biometric identification systems in publicly accessible spaces for purposes other than law enforcement , including by competent authorities , should not be covered by the specific framework regarding such use for the purpose of law enforcement set by this regulation. such use for purposes other than law enforcement should therefore not be subject to the requirement of an authorisation under this regulation and the applicable detailed rules of national law that may give effect to it.


### (33) technical inaccuracies of ai systems intended for the remote biometric identification of natural persons can lead to biased results and entail discriminatory effects. this is particularly relevant when it comes to age , ethnicity , sex or disabilities. therefore , ‘real-time’ and ‘post’ remote biometric identification systems should be classified as high-risk. in view of the risks that they pose , both types of remote biometric identification systems should be subject to specific requirements on logging capabilities and human oversight. ### (33) technical inaccuracies of ai systems intended for the remote biometric identification of natural persons can lead to biased results and entail discriminatory effects. this is particularly relevant when it comes to age , ethnicity , sex or disabilities. therefore , ‘real-time’ and ‘post’ remote biometric identification systems should be classified as high-risk. in view of the risks that they pose , both types of remote biometric identification systems should be subject to specific requirements on logging capabilities and human oversight. the high risk of non-remote biometric identification systems intended to be used in publicly accessible spaces , workplaces and education and training institutions should be determined on a case-by-case basis.


### (33) technical inaccuracies of ai systems intended for the remote biometric identification of natural persons can lead to biased results and entail discriminatory effects. this is particularly relevant when it comes to age , ethnicity , sex or disabilities. therefore , ‘real-time’ and ‘post’ remote biometric identification systems should be classified as high-risk. in view of the risks that they pose , both types of remote biometric identification systems should be subject to specific requirements on logging capabilities and human oversight. ### (33) technical inaccuracies of ai systems intended for the remote biometric identification of natural persons can lead to biased results and entail discriminatory effects. this is particularly relevant when it comes to age , ethnicity , sex or disabilities. therefore , ‘real-time’ and ‘post’ remote biometric identification systems should be classified as high-risk , except for the purpose of remote client on-boarding or verification of a user through a device. in view of the risks that they may pose , both types of remote biometric identification systems should be subject to specific requirements on logging capabilities and , when appropriate and justified by a proven added value to the protection of health , safety and fundamental rights , human oversight.


### (33) technical inaccuracies of ai systems intended for the remote biometric identification of natural persons can lead to biased results and entail discriminatory effects. this is particularly relevant when it comes to age , ethnicity , sex or disabilities. therefore , ‘real-time’ and ‘post’ remote biometric identification systems should be classified as high-risk. in view of the risks that they pose , both types of remote biometric identification systems should be subject to specific requirements on logging capabilities and human oversight. ### (33) technical inaccuracies of ai systems intended for the biometric identification of natural persons , including remote biometric identification , can lead to biased results and entail discriminatory effects. this is particularly relevant when it comes to age , ethnicity , sex or disabilities. therefore , ‘real-time’ and ‘post’ remote biometric identification systems , including remote biometric identification , should be classified as high-risk. in view of the risks that they pose , both types of remote biometric identification systems should be subject to specific requirements on logging capabilities and human oversight.


### (34) as regards the management and operation of critical infrastructure , it is appropriate to classify as high-risk the ai systems intended to be used as safety components in the management and operation of road traffic and the supply of water , gas , heating and electricity , since their failure or malfunctioning may put at risk the life and health of persons at large scale and lead to appreciable disruptions in the ordinary conduct of social and economic activities. ### (34) as regards the management and operation of critical infrastructure , it is appropriate to classify as high-risk the ai systems intended to be used as safety or security components in the management and operation of road traffic and the supply of water , gas , heating and electricity , since their failure or malfunctioning may infringe the security and integrity of such critical infrastructure and thus put at risk the life and health of persons at large scale and lead to appreciable disruptions in the ordinary conduct of social and economic activities.


### (37) another area in which the use of ai systems deserves special consideration is the access to and enjoyment of certain essential private and public services and benefits necessary for people to fully participate in society or to improve one’s standard of living. in particular , ai systems used to evaluate the credit score or creditworthiness of natural persons should be classified as high-risk ai systems , since they determine those persons’ access to financial resources or essential services such as housing , electricity , and telecommunication services. ai systems used for this purpose may lead to discrimination of persons or groups and perpetuate historical patterns of discrimination , for example based on racial or ethnic origins , disabilities , age , sexual orientation , or create new forms of discriminatory impacts. considering the very limited scale of the impact and the available alternatives on the market , it is appropriate to exempt ai systems for the purpose of creditworthiness assessment and credit scoring when put into service by small-scale providers for their own use. natural persons applying for or receiving public assistance benefits and services from public authorities are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities. if ai systems are used for determining whether such benefits and services should be denied , reduced , revoked or reclaimed by authorities , they may have a significant impact on persons’ livelihood and may infringe their fundamental rights , such as the right to social protection , non-discrimination , human dignity or an effective remedy. those systems should therefore be classified as high-risk. nonetheless , this regulation should not hamper the development and use of innovative approaches in the public administration , which would stand to benefit from a wider use of compliant and safe ai systems , provided that those systems do not entail a high risk to legal and natural persons. finally , ai systems used to dispatch or establish priority in the dispatching of emergency first response services should also be classified as high-risk since they make decisions in very critical situations for the life and health of persons and their property. ### (37) another area in which the use of ai systems deserves special consideration is the access to and enjoyment of certain essential private and public services and benefits necessary for people to fully participate in society or to improve one’s standard of living. in particular , ai systems used to evaluate the credit score or creditworthiness of natural persons should be classified as high-risk ai systems , since they determine those persons’ access to financial resources or essential services such as housing , electricity , and telecommunication services. ai systems used for this purpose may lead to discrimination of persons or groups and perpetuate historical patterns of discrimination , for example based on racial or ethnic origins , disabilities , age , sexual orientation , or create new forms of discriminatory impacts. considering the very limited scale of the impact and the available alternatives on the market , it is appropriate to exempt ai systems for the purpose of creditworthiness assessment and credit scoring when put into service by small-scale providers for their own use. due to the fact that ai systems related to low-value credits for the purchase of movables do not cause high risk , it is proposed to exclude this category from the scope of high-risk ai category as well. . natural persons applying for or receiving public assistance benefits and services from public authorities are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities. if ai systems are used for determining whether such benefits and services should be denied , reduced , revoked or reclaimed by authorities , they may have a significant impact on persons’ livelihood and may infringe their fundamental rights , such as the right to social protection , non-discrimination , human dignity or an effective remedy. those systems should therefore be classified as high-risk. nonetheless , this regulation should not hamper the development and use of innovative approaches in the public administration , which would stand to benefit from a wider use of compliant and safe ai systems , provided that those systems do not entail a high risk to legal and natural persons. finally , ai systems used to dispatch or establish priority in the dispatching of emergency first response services should also be classified as high-risk since they make decisions in very critical situations for the life and health of persons and their property.


### (37) another area in which the use of ai systems deserves special consideration is the access to and enjoyment of certain essential private and public services and benefits necessary for people to fully participate in society or to improve one’s standard of living. in particular , ai systems used to evaluate the credit score or creditworthiness of natural persons should be classified as high-risk ai systems , since they determine those persons’ access to financial resources or essential services such as housing , electricity , and telecommunication services. ai systems used for this purpose may lead to discrimination of persons or groups and perpetuate historical patterns of discrimination , for example based on racial or ethnic origins , disabilities , age , sexual orientation , or create new forms of discriminatory impacts. considering the very limited scale of the impact and the available alternatives on the market , it is appropriate to exempt ai systems for the purpose of creditworthiness assessment and credit scoring when put into service by small-scale providers for their own use. natural persons applying for or receiving public assistance benefits and services from public authorities are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities. if ai systems are used for determining whether such benefits and services should be denied , reduced , revoked or reclaimed by authorities , they may have a significant impact on persons’ livelihood and may infringe their fundamental rights , such as the right to social protection , non-discrimination , human dignity or an effective remedy. those systems should therefore be classified as high-risk. nonetheless , this regulation should not hamper the development and use of innovative approaches in the public administration , which would stand to benefit from a wider use of compliant and safe ai systems , provided that those systems do not entail a high risk to legal and natural persons. finally , ai systems used to dispatch or establish priority in the dispatching of emergency first response services should also be classified as high-risk since they make decisions in very critical situations for the life and health of persons and their property. ### (37) another area in which the use of ai systems deserves special consideration is the access to and enjoyment of certain essential private and public services and benefits necessary for people to fully participate in society or to improve one’s standard of living. in particular , ai systems that automatically generate models used to evaluate the credit score or creditworthiness of natural persons should be classified as high-risk ai systems , since they determine those persons’ access to financial resources or essential services such as housing , electricity , and telecommunication services. in contrast , ancillary applications to those systems determining whether an individual should be granted access to credit , such as ai applications used for the acceleration of the credit disbursement process , in the valuation of collateral , or for the internal process efficiency , as well as other subsequent applications based on the credit scoring which do not create high risks for individuals should be exempt from the scope. ai systems used to evaluate the credit score or creditworthiness may lead to discrimination of persons or groups and perpetuate historical patterns of discrimination , for example based on racial or ethnic origins , disabilities , age , sexual orientation , or create new forms of discriminatory impacts. natural persons applying for or receiving public assistance benefits and services from public authorities are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities. if ai systems are used for determining whether such benefits and services should be denied , reduced , revoked or reclaimed by authorities , they may have a significant impact on persons’ livelihood and may infringe their fundamental rights , such as the right to social protection , non-discrimination , human dignity or an effective remedy. those systems should therefore be classified as high-risk. in fact , this regulation should not hamper the development and use of innovative approaches in the public administration , which would stand to benefit from a wider use of compliant and safe ai systems , provided that those systems do not entail a high risk to legal and natural persons. finally , ai systems used to dispatch or establish priority in the dispatching of emergency first response services should also be classified as high-risk since they make decisions in very critical situations for the life and health of persons and their property.


### (37) another area in which the use of ai systems deserves special consideration is the access to and enjoyment of certain essential private and public services and benefits necessary for people to fully participate in society or to improve one’s standard of living. in particular , ai systems used to evaluate the credit score or creditworthiness of natural persons should be classified as high-risk ai systems , since they determine those persons’ access to financial resources or essential services such as housing , electricity , and telecommunication services. ai systems used for this purpose may lead to discrimination of persons or groups and perpetuate historical patterns of discrimination , for example based on racial or ethnic origins , disabilities , age , sexual orientation , or create new forms of discriminatory impacts. considering the very limited scale of the impact and the available alternatives on the market , it is appropriate to exempt ai systems for the purpose of creditworthiness assessment and credit scoring when put into service by small-scale providers for their own use. natural persons applying for or receiving public assistance benefits and services from public authorities are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities. if ai systems are used for determining whether such benefits and services should be denied , reduced , revoked or reclaimed by authorities , they may have a significant impact on persons’ livelihood and may infringe their fundamental rights , such as the right to social protection , non-discrimination , human dignity or an effective remedy. those systems should therefore be classified as high-risk. nonetheless , this regulation should not hamper the development and use of innovative approaches in the public administration , which would stand to benefit from a wider use of compliant and safe ai systems , provided that those systems do not entail a high risk to legal and natural persons. finally , ai systems used to dispatch or establish priority in the dispatching of emergency first response services should also be classified as high-risk since they make decisions in very critical situations for the life and health of persons and their property. ### (37) another area in which the use of ai systems deserves special consideration is the access to and enjoyment of certain essential private and public services and benefits necessary for people to fully participate in society or to improve one’s standard of living. in particular , ai systems used to evaluate the credit score or creditworthiness of natural persons should be classified as high-risk ai systems , since they determine those persons’ access to financial resources or essential services such as housing , electricity , healthcare and telecommunication services. ai systems used for this purpose may lead to discrimination of persons or groups and perpetuate historical patterns of discrimination , for example based on racial or ethnic origins , disabilities , age , sexual orientation , or create new forms of discriminatory impacts. considering the very limited scale of the impact and the available alternatives on the market , it is appropriate to exempt ai systems for the purpose of creditworthiness assessment and credit scoring when put into service by small-scale providers for their own use. natural persons applying for or receiving public assistance benefits and services from public authorities are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities. if ai systems are used for determining whether such benefits and services should be denied , reduced , revoked or reclaimed by authorities , they may have a significant impact on persons’ livelihood , health and wellbeing , and may infringe their fundamental rights , such as the right to social protection , non-discrimination , human dignity or an effective remedy. those systems should therefore be classified as high-risk. nonetheless , this regulation should not hamper the development and use of innovative approaches in the public administration , which would stand to benefit from a wider use of compliant and safe ai systems , provided that those systems do not entail a high risk to legal and natural persons. finally , ai systems used to dispatch or establish priority in the dispatching of emergency first response services , disease prevention , diagnosis , control and treatment should also be classified as high-risk since they make decisions in very critical situations for the life and health of persons and their property.


### (37) another area in which the use of ai systems deserves special consideration is the access to and enjoyment of certain essential private and public services and benefits necessary for people to fully participate in society or to improve one’s standard of living. in particular , ai systems used to evaluate the credit score or creditworthiness of natural persons should be classified as high-risk ai systems , since they determine those persons’ access to financial resources or essential services such as housing , electricity , and telecommunication services. ai systems used for this purpose may lead to discrimination of persons or groups and perpetuate historical patterns of discrimination , for example based on racial or ethnic origins , disabilities , age , sexual orientation , or create new forms of discriminatory impacts. considering the very limited scale of the impact and the available alternatives on the market , it is appropriate to exempt ai systems for the purpose of creditworthiness assessment and credit scoring when put into service by small-scale providers for their own use. natural persons applying for or receiving public assistance benefits and services from public authorities are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities. if ai systems are used for determining whether such benefits and services should be denied , reduced , revoked or reclaimed by authorities , they may have a significant impact on persons’ livelihood and may infringe their fundamental rights , such as the right to social protection , non-discrimination , human dignity or an effective remedy. those systems should therefore be classified as high-risk. nonetheless , this regulation should not hamper the development and use of innovative approaches in the public administration , which would stand to benefit from a wider use of compliant and safe ai systems , provided that those systems do not entail a high risk to legal and natural persons. finally , ai systems used to dispatch or establish priority in the dispatching of emergency first response services should also be classified as high-risk since they make decisions in very critical situations for the life and health of persons and their property. ### (37) another area in which the use of ai systems deserves special consideration is the access to and enjoyment of certain essential private and public services , including healthcare and benefits necessary for people to fully participate in society or to improve one’s standard of living. in particular , ai systems used to evaluate the credit score or creditworthiness of natural persons should be classified as high-risk ai systems , since they determine those persons’ access to financial resources or essential services such as housing , electricity , and telecommunication services. ai systems used for this purpose may lead to discrimination of persons or groups and perpetuate historical patterns of discrimination , for example based on racial or ethnic origins , disabilities , age , sexual orientation , or create new forms of discriminatory impacts. considering the very limited scale of the impact and the available alternatives on the market , it is appropriate to exempt ai systems for the purpose of creditworthiness assessment and credit scoring when put into service by small-scale providers for their own use. natural persons applying for or receiving public assistance benefits and services from public authorities are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities. if ai systems are used for determining whether such benefits and services should be denied , reduced , revoked or reclaimed by authorities , they may have a significant impact on persons’ livelihood and may infringe their fundamental rights , such as the right to social protection , non-discrimination , human dignity or an effective remedy. those systems should therefore be classified as high-risk. nonetheless , this regulation should not hamper the development and use of innovative approaches in the public administration , which would stand to benefit from a wider use of compliant and safe ai systems , provided that those systems do not entail a high risk to legal and natural persons. finally , ai systems used to dispatch or establish priority in the dispatching of emergency first response services should also be classified as high-risk since they make decisions in very critical situations for the life and health of persons and their property.


### (37) another area in which the use of ai systems deserves special consideration is the access to and enjoyment of certain essential private and public services and benefits necessary for people to fully participate in society or to improve one’s standard of living. in particular , ai systems used to evaluate the credit score or creditworthiness of natural persons should be classified as high-risk ai systems , since they determine those persons’ access to financial resources or essential services such as housing , electricity , and telecommunication services. ai systems used for this purpose may lead to discrimination of persons or groups and perpetuate historical patterns of discrimination , for example based on racial or ethnic origins , disabilities , age , sexual orientation , or create new forms of discriminatory impacts. considering the very limited scale of the impact and the available alternatives on the market , it is appropriate to exempt ai systems for the purpose of creditworthiness assessment and credit scoring when put into service by small-scale providers for their own use. natural persons applying for or receiving public assistance benefits and services from public authorities are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities. if ai systems are used for determining whether such benefits and services should be denied , reduced , revoked or reclaimed by authorities , they may have a significant impact on persons’ livelihood and may infringe their fundamental rights , such as the right to social protection , non-discrimination , human dignity or an effective remedy. those systems should therefore be classified as high-risk. nonetheless , this regulation should not hamper the development and use of innovative approaches in the public administration , which would stand to benefit from a wider use of compliant and safe ai systems , provided that those systems do not entail a high risk to legal and natural persons. finally , ai systems used to dispatch or establish priority in the dispatching of emergency first response services should also be classified as high-risk since they make decisions in very critical situations for the life and health of persons and their property. ### (37) another area in which the use of ai systems deserves special consideration is the access to and enjoyment of certain essential private and public services and benefits necessary for people to fully participate in society or to improve one’s standard of living. in particular , ai systems used to evaluate the credit score or creditworthiness of natural persons should be classified as high-risk ai systems , since they determine those persons’ access to financial resources or essential services such as healthcare , housing , electricity , and telecommunication services. ai systems used for this purpose may lead to discrimination of persons or groups and perpetuate historical patterns of discrimination , for example based on racial or ethnic origins , disabilities , age , sexual orientation , or create new forms of discriminatory impacts. considering the very limited scale of the impact and the available alternatives on the market , it is appropriate to exempt ai systems for the purpose of creditworthiness assessment and credit scoring when put into service by small-scale providers for their own use. natural persons applying for or receiving public assistance benefits and services from public authorities are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities. if ai systems are used for determining whether such benefits and services should be denied , reduced , revoked or reclaimed by authorities , they may have a significant impact on persons’ livelihood , health and may infringe their fundamental rights , such as the right to social protection , non-discrimination , human dignity or an effective remedy. those systems should therefore be classified as high-risk. nonetheless , this regulation should not hamper the development and use of innovative approaches in the public administration , which would stand to benefit from a wider use of compliant and safe ai systems , provided that those systems do not entail a high risk to legal and natural persons. finally , ai systems used to dispatch or establish priority in the dispatching of emergency first response services should also be classified as high-risk since they make decisions in very critical situations for the life and health of persons and their property.


### (43) requirements should apply to high-risk ai systems as regards the quality of data sets used , technical documentation and record-keeping , transparency and the provision of information to users , human oversight , and robustness , accuracy and cybersecurity. those requirements are necessary to effectively mitigate the risks for health , safety and fundamental rights , as applicable in the light of the intended purpose of the system , and no other less trade restrictive measures are reasonably available , thus avoiding unjustified restrictions to trade. ### (43) requirements should apply to high-risk ai systems as regards the quality of data sets used , technical documentation and record-keeping , transparency and the provision of information to users , human oversight , and robustness , accuracy and cybersecurity. those requirements are necessary to effectively mitigate the risks for health , safety and fundamental rights , as applicable in the light of the intended purpose of the system , and no other less trade restrictive measures are reasonably available , thus avoiding unjustified restrictions to trade. to avoid any potential misalignment or duplication , the commission should clearly determine where any relevant sectoral legislation may take precedence concerning data governance and any associated management practices or quality criteria.


### (44) high data quality is essential for the performance of many ai systems , especially when techniques involving the training of models are used , with a view to ensure that the high-risk ai system performs as intended and safely and it does not become the source of discrimination prohibited by union law. high quality training , validation and testing data sets require the implementation of appropriate data governance and management practices. training , validation and testing data sets should be sufficiently relevant , representative and free of errors and complete in view of the intended purpose of the system. they should also have the appropriate statistical properties , including as regards the persons or groups of persons on which the high-risk ai system is intended to be used. in particular , training , validation and testing data sets should take into account , to the extent required in the light of their intended purpose , the features , characteristics or elements that are particular to the specific geographical , behavioural or functional setting or context within which the ai system is intended to be used. in order to protect the right of others from the discrimination that might result from the bias in ai systems , the providers shouldbe able to process also special categories of personal data , as a matter of substantial public interest , in order to ensure the bias monitoring , detection and correction in relation to high-risk ai systems. ### (44) high data quality is essential for the performance of many ai systems , especially when techniques involving the training of models are used , with a view to ensure that the high-risk ai system performs as intended and safely and it does not become the source of discrimination prohibited by union law. high quality training , validation and testing data sets require the implementation of appropriate data governance and management practices. training , validation and testing data sets should be sufficiently relevant and complete in view of the intended purpose of the system. they should also have the appropriate statistical properties , including as regards the persons or groups of persons on which the high-risk ai system is intended to be used. in particular , training , validation and testing data sets should take into account , to the extent required in the light of their intended purpose , the features , characteristics or elements that are particular to the specific geographical , behavioural or functional setting or context within which the ai system is intended to be used. in order to protect the right of others from the discrimination that might result from the bias in ai systems , the providers should be able to process also special categories of personal data , as a matter of substantial public interest , in order to ensure the bias monitoring , detection and correction in relation to high-risk ai systems. in practice , a sufficient solution for bias monitoring could be achieved by abiding by state-of-the-art security and privacy-preserving standards with regards to data management.


### (44) high data quality is essential for the performance of many ai systems , especially when techniques involving the training of models are used , with a view to ensure that the high-risk ai system performs as intended and safely and it does not become the source of discrimination prohibited by union law. high quality training , validation and testing data sets require the implementation of appropriate data governance and management practices. training , validation and testing data sets should be sufficiently relevant , representative and free of errors and complete in view of the intended purpose of the system. they should also have the appropriate statistical properties , including as regards the persons or groups of persons on which the high-risk ai system is intended to be used. in particular , training , validation and testing data sets should take into account , to the extent required in the light of their intended purpose , the features , characteristics or elements that are particular to the specific geographical , behavioural or functional setting or context within which the ai system is intended to be used. in order to protect the right of others from the discrimination that might result from the bias in ai systems , the providers shouldbe able to process also special categories of personal data , as a matter of substantial public interest , in order to ensure the bias monitoring , detection and correction in relation to high-risk ai systems. ### (44) high data quality and having simple and accessible data plays a vital role in providing structure and ground truth for ai and are essential for purpose-ready data analytics and the performance of many ai systems , especially when techniques involving the training of models are used , with a view to ensure that the high-risk ai system performs as intended and safely and it does not become the source of discrimination prohibited by union law. to achieve simple access to and usability of high quality data for ai , the commission should examine ways to facilitate the lawful processing of personal data to train legitimate ai systems by appropriate amendments to applicable laws. high quality training , validation and testing data sets require the implementation of appropriate data governance and management practices. training , machine learning validation and testing data sets should be sufficiently relevant and representative in view of the intended purpose of the system. they should also have the appropriate statistical properties , including as regards the persons or groups of persons on which the high-risk ai system is intended to be used. in particular , training , machine learning validation and testing data sets should take into account , to the extent required in the light of their intended purpose , the features , characteristics or elements that are particular to the specific geographical , behavioural or functional setting or context within which the ai system is intended to be used. if it is necessary for the aforementioned purpose to use existing sets of data that includes personal data originally collected and stored for a different purpose , their use for the aforementioned purpose should be deemed compatible with the original purpose so long as the personal data is not transferred to any third party. in order to protect the right of others from the discrimination that might result from the bias in ai systems , the providers should be able to process also special categories of personal data , as a matter of substantial public interest , in order to ensure the bias monitoring , detection and correction in relation to high-risk ai systems.


### (44) high data quality is essential for the performance of many ai systems , especially when techniques involving the training of models are used , with a view to ensure that the high-risk ai system performs as intended and safely and it does not become the source of discrimination prohibited by union law. high quality training , validation and testing data sets require the implementation of appropriate data governance and management practices. training , validation and testing data sets should be sufficiently relevant , representative and free of errors and complete in view of the intended purpose of the system. they should also have the appropriate statistical properties , including as regards the persons or groups of persons on which the high-risk ai system is intended to be used. in particular , training , validation and testing data sets should take into account , to the extent required in the light of their intended purpose , the features , characteristics or elements that are particular to the specific geographical , behavioural or functional setting or context within which the ai system is intended to be used. in order to protect the right of others from the discrimination that might result from the bias in ai systems , the providers shouldbe able to process also special categories of personal data , as a matter of substantial public interest , in order to ensure the bias monitoring , detection and correction in relation to high-risk ai systems. ### (44) high data quality is essential for the performance of many ai systems , especially when techniques involving the training of models are used , with a view to ensure that the high-risk ai system performs as intended and safely and it does not become the source of discrimination prohibited by union law. high quality training , validation and testing data sets require the implementation of appropriate data governance and management practices. training , validation and testing data sets should be sufficiently relevant , representative as complete and close to zero error as possible. a procedure to check data and completeness in view of the intended purpose of the system should be implemented. they should also have the appropriate statistical properties , including as regards the persons or groups of persons on which the high-risk ai system is intended to be used. in particular , training , validation and testing data sets should take into account , to the extent required in the light of their intended purpose , the features , characteristics or elements that are particular to the specific geographical , behavioural or functional setting or context within which the ai system is intended to be used. in order to protect the right of others from the discrimination that might result from the unfair bias in ai systems , the providers shouldbe able to process also special categories of personal data , as a matter of substantial public interest , in order to ensure the unfair bias monitoring , detection and correction in relation to high-risk ai systems.


### (44) high data quality is essential for the performance of many ai systems , especially when techniques involving the training of models are used , with a view to ensure that the high-risk ai system performs as intended and safely and it does not become the source of discrimination prohibited by union law. high quality training , validation and testing data sets require the implementation of appropriate data governance and management practices. training , validation and testing data sets should be sufficiently relevant , representative and free of errors and complete in view of the intended purpose of the system. they should also have the appropriate statistical properties , including as regards the persons or groups of persons on which the high-risk ai system is intended to be used. in particular , training , validation and testing data sets should take into account , to the extent required in the light of their intended purpose , the features , characteristics or elements that are particular to the specific geographical , behavioural or functional setting or context within which the ai system is intended to be used. in order to protect the right of others from the discrimination that might result from the bias in ai systems , the providers shouldbe able to process also special categories of personal data , as a matter of substantial public interest , in order to ensure the bias monitoring , detection and correction in relation to high-risk ai systems. ### (44) high data quality is essential for the performance of many ai systems , especially when techniques involving the training of models are used , with a view to ensure that the high-risk ai system performs as intended and safely and it does not become the source of discrimination prohibited by union law. high quality training , validation and testing data sets require the implementation of appropriate data governance and management practices. training , validation and testing data sets should be sufficiently relevant , representative in view of the intended purpose of the system. they should also have the appropriate statistical properties , including as regards the persons or groups of persons on which the high-risk ai system is intended to be used. in particular , training , validation and testing data sets should take into account , to the extent required in the light of their intended purpose , the features , characteristics or elements that are particular to the specific geographical , behavioural or functional setting or context within which the ai system is intended to be used. in order to protect the right of others from the discrimination that might result from the bias in ai systems , the providers shouldbe able to process also special categories of personal data , as a matter of substantial public interest , in order to ensure the bias monitoring , detection and correction in relation to high-risk ai systems.


### (48) high-risk ai systems should be designed and developed in such a way that natural persons can oversee their functioning. for this purpose , appropriate human oversight measures should be identified by the provider of the system before its placing on the market or putting into service. in particular , where appropriate , such measures should guarantee that the system is subject to in-built operational constraints that cannot be overridden by the system itself and is responsive to the human operator , and that the natural persons to whom human oversight has been assigned have the necessary competence , training and authority to carry out that role. ### (48) high-risk ai systems should be designed and developed in such a way that natural persons may , when appropriate , oversee their functioning. for this purpose , when it brings proven added value to the protection of health , safety and fundamental rights , appropriate human oversight measures should be identified by the provider of the system before its placing on the market or putting into service. in particular , where appropriate , such measures should guarantee that the system is subject to in-built operational constraints and are responsive to the human operator during the expected lifetime of the device where necessary to reduce risks as far as possible and achieve performance in consideration of the generally acknowledged state-of-the-art and technological and scientific progress , and that the natural persons to whom human oversight has been assigned have the necessary competence , training and authority to carry out that role. by way of derogation regarding high-risk ai systems within the scope of regulation (eu) 2017/745 and regulation (eu) 2017/746 of the european parliament and of the council , the established benefit-risk ratio requirements under the sectoral medical device legislation should apply.


### (48) high-risk ai systems should be designed and developed in such a way that natural persons can oversee their functioning. for this purpose , appropriate human oversight measures should be identified by the provider of the system before its placing on the market or putting into service. in particular , where appropriate , such measures should guarantee that the system is subject to in-built operational constraints that cannot be overridden by the system itself and is responsive to the human operator , and that the natural persons to whom human oversight has been assigned have the necessary competence , training and authority to carry out that role. ### (48) high-risk ai systems should be designed and developed in such a way that natural persons may , when appropriate , oversee their functioning. for this purpose , when it brings proven added value to the protection of health , safety and fundamental rights , appropriate human oversight measures should be identified by the provider of the system before its placing on the market or putting into service. in particular , where appropriate , such measures should guarantee that the system is subject to in-built operational constraints and are responsive to the human operator during the expected lifetime of the device where necessary to reduce risks as far as possible and achieve performance in consideration of the generally acknowledged state-of-the-art technological and scientific progress , and that the natural persons to whom human oversight has been assigned have the necessary competence , training and authority to carry out that role. by way of derogation regarding high-risk ai systems within the scope of regulation (eu) 2017/745 and regulation (eu) 2017/746 of the european parliament and of the council , the established benefit-risk ratio requirements under the sectoral medical device legislation should apply.


### (48) high-risk ai systems should be designed and developed in such a way that natural persons can oversee their functioning. for this purpose , appropriate human oversight measures should be identified by the provider of the system before its placing on the market or putting into service. in particular , where appropriate , such measures should guarantee that the system is subject to in-built operational constraints that cannot be overridden by the system itself and is responsive to the human operator , and that the natural persons to whom human oversight has been assigned have the necessary competence , training and authority to carry out that role. ### (48) high-risk ai systems should be designed and developed in such a way that natural persons can oversee their functioning. for this purpose , appropriate human oversight measures should be identified by the provider of the system before its placing on the market or putting into service. in particular , where appropriate , such measures should guarantee that the system is subject to in-built operational constraints that cannot be overridden by the system itself and is responsive to the human operator , and that the natural persons to whom human oversight has been assigned have the necessary competence , training and authority to carry out that role. appropriate human oversight and any subsequent intervention should not result in the intended function of the ai system being affected in a way that risks health , safety or fundamental rights , as applicable in the light of the intended purpose of the system.