### 8. explains that there is therefore a race for ai leadership within the global tech race; points out that the countries that master ai will gain key advantages; highlights , however , that ai is not a technology with magical powers but rather an efficient tool that we can put to good use; states that the rise of ai likewise does not require us to completely rewrite our laws to counter new kind of threats or to prevent intelligent machines from taking over; believes that although ai is indeed reshaping the world as we know it , the reality is much less dramatic and most developments in the field of ai are positive; ### 8. observes that the implications of ai are such that there is a competition for ai leadership within the global tech race; points out that the countries with sufficient ai capabilities will gain key advantages; highlights , however , that ai is not an omnipotent technology but rather an efficient tool that should be put to good use for the benefit of society; states that the rise of ai likewise does not require us to completely rewrite all our laws but requires an update of relevant legislation; believes that although ai is indeed reshaping the world as we know it , many developments in the field of ai are positive;


### 9. explains that ai is actually an umbrella term that covers a wide range of old and new technologies that often have little more in common than being guided by a given set of human-defined objectives and having some degree of autonomy in their actions; notes that while some of these technologies are already in widespread use , others are still under development or are even just speculative concepts that may or may not exist in the future; ### 9. explains that the term "ai" is actually an umbrella term that covers a wide range of old and new techniques and approaches better understood as "artificial intelligence systems" that refer to any machine-based system that can , for a given set of human-defined objectives , make predictions , recommendations , or decisions influencing real or virtual environments. ai systems are designed to operate with varying levels of autonomy9a; notes that while some of these technologies are already in widespread use , others are still under development or are even just speculative concepts that may or may not exist in the future;


### 9. explains that ai is actually an umbrella term that covers a wide range of old and new technologies that often have little more in common than being guided by a given set of human-defined objectives and having some degree of autonomy in their actions; notes that while some of these technologies are already in widespread use , others are still under development or are even just speculative concepts that may or may not exist in the future; ### 9. points out that ai is actually an umbrella term that covers a wide range of old and new technologies that often have little more in common than being guided by a given set of human-defined objectives and having some degree of autonomy in their actions; notes that while some of these technologies are already in widespread use , others are still under development or are even just speculative concepts that may or may not exist in the future;


### 11. notes that in the second wave , the automated learning processes of algorithms based on the processing of large amounts of high-quality data , the ability to bring together inputs from multiple radars , lidars and cameras to form a single image of the environment , and the identification of patterns made ai systems more complex , autonomous and opaque; stresses that current ai can therefore be broken down into many different sub-domains and techniques , whereby deep learning is for instance a subfield of machine learning , which itself is a subfield of ai; ### 11. notes that in the second wave , the automated learning processes of algorithms based on the processing of large amounts of high-quality data , the ability to bring together inputs from multiple radars , lidars and cameras to form a single image of the environment , and the identification of patterns made ai systems more complex , autonomous and opaque , which leads to less explainable outcomes; stresses that current ai can therefore be broken down into many different sub-domains and techniques , whereby deep learning is for instance a subfield of machine learning , which itself is a subfield of ai;


### 12. notes that although today’s ai has become much more powerful than symbolic ai , it can still only solve tasks in domain-specific niches such as chess or facial recognition and does not understand the actions it performs; points out that it is therefore referred to as ‘narrow’ or ‘weak’ ai and is still not more than a tool that provides recommendations and predictions; explains that self-driving cars operate , for instance , through a combination of various one-task ai systems that together are able to provide a three-dimensional map of the surroundings of the vehicle so that its operating system can make the appropriate decisions; ### 12. notes that although today’s ai has become much more powerful than symbolic ai , thanks to the significant increases in computing capacities , it can still only solve clearly defined tasks in domain-specific niches such as chess or image recognition , does not understand the actions it performs nor context and can therefore make mistakes , for example identifying patterns in spurious correlations; adds that ai should not be anthropomorphised with misleading metaphors; notes that ai is not capable of feeling emotions nor having a conscience , nor can it communicate with other “narrow” ai applications; points out that it is therefore referred to as ‘narrow’ or ‘weak’ ai and is still only a tool that provides recommendations and predictions;


### 12. notes that although today’s ai has become much more powerful than symbolic ai , it can still only solve tasks in domain-specific niches such as chess or facial recognition and does not understand the actions it performs; points out that it is therefore referred to as ‘narrow’ or ‘weak’ ai and is still not more than a tool that provides recommendations and predictions; explains that self-driving cars operate , for instance , through a combination of various one-task ai systems that together are able to provide a three-dimensional map of the surroundings of the vehicle so that its operating system can make the appropriate decisions; ### 12. notes that although today’s ai has become much more powerful than symbolic ai , it can still only solve tasks in domain-specific niches such as chess or facial recognition and its programming is not designed to fully recognise the actions that the ai system performs; points out that it is therefore referred to as ‘narrow’ or ‘weak’ ai and is still not more than a tool that provides recommendations and predictions; explains that self-driving cars operate , for instance , through a combination of various one-task ai systems that together are able to provide a three-dimensional map of the surroundings of the vehicle so that its operating system can make the appropriate decisions;


### 13. highlights that many fears linked to ai are based on hypothetical concepts such as general ai , artificial superintelligence and singularity which could , in theory , lead to a power shift from humans to ai and create machines that could even break free from human control; stresses , however , that there are significant doubts as to whether this speculative ai can even be achieved with our technologies and scientific laws; ### 13. underlines that although the possibility of a general artificial intelligence is remote for the foreseeable future , ai-based decision-making can present risks that need to be seriously addressed by legislators; points out that several ai experts believe that marginal improvements to current machine learning systems may be able to supersede the human intellectual capacities in a wide range of tasks if given more data and computing power;


### 14. underlines that , on the contrary , the vast majority of ai systems currently in use , are almost or even completely risk-free; refers , for instance , to automatic translations , ‘eureka machines’ , gaming machines and robots that execute repetitive manufacturing processes; concludes that only a very small number of use cases can be categorised as risky and that only such cases require regulatory action and effective safeguards; ### 14. underlines that , on the contrary , the majority of ai systems currently in use , is low-risk; refers , for instance , to automatic translations , video games and robots that execute repetitive manufacturing processes;


### 14. underlines that , on the contrary , the vast majority of ai systems currently in use , are almost or even completely risk-free; refers , for instance , to automatic translations , ‘eureka machines’ , gaming machines and robots that execute repetitive manufacturing processes; concludes that only a very small number of use cases can be categorised as risky and that only such cases require regulatory action and effective safeguards; ### 14. underlines that , on the contrary , the vast majority of ai systems currently in use , are almost or even completely risk-free; refers , for instance , to automatic translations , ‘eureka machines’ , gaming machines and robots that execute repetitive manufacturing processes;


### 15. considers that the public debate should therefore be more focused on the enormous potential of ai; believes that ai offers humankind the unique chance to improve almost every area of our lives , from combating global societal challenges such as climate change , pandemics and starvation , to enhancing quality of life through personalised medicine , fitness programmes and assisted living; ### 15. considers that the public debate should therefore be more focused on the enormous potential of ai; believes that ai offers humankind the unique chance to improve almost every area of our lives , from combating global societal challenges such as climate change , pandemics and starvation , to enhancing quality of life through personalised medicine , fitness programmes and assisted living; is of the opinion that the public debate should continue focusing on the development of trustworthy ai based on fundamental european values and the principle that ai and robotics should be developed to complement humans and prioritise and promote sustainable human-centred development; highlights that the agreed ai ethical principles and requirements should be operationalised in all domains of ai application15a;


### 15. considers that the public debate should therefore be more focused on the enormous potential of ai; believes that ai offers humankind the unique chance to improve almost every area of our lives , from combating global societal challenges such as climate change , pandemics and starvation , to enhancing quality of life through personalised medicine , fitness programmes and assisted living; ### 15. believes that ai offers humankind the unique chance to improve a significant number of areas of our lives , from combating global societal challenges such as climate change , pandemics and starvation , to enhancing quality of life through personalised medicine , fitness programmes and assisted living; stresses that in most of those areas , ai should be seen as an auxiliary tool for users and professionals , augmenting the capabilities of humans without impeding their ability to freely act and decide;


### 15. considers that the public debate should therefore be more focused on the enormous potential of ai; believes that ai offers humankind the unique chance to improve almost every area of our lives , from combating global societal challenges such as climate change , pandemics and starvation , to enhancing quality of life through personalised medicine , fitness programmes and assisted living; ### 15. considers at the same time that ai holds enormous potential , as it offers countless opportunities to improve many areas of our lives , from combating global societal challenges such as climate change , pandemics and starvation , to contributing to the sdgs , to enhancing quality of life through personalised medicine and assisted living;


### 16. explains that the present report addresses six ai case studies in detail , outlining the opportunities offered by ai in the respective sector , the risks to be addressed and the obstacles currently preventing us from fully harnessing the benefits of ai; highlights that the case studies represent some of the most important ai use cases and , at the same time , reflect the main topics of the public hearings held by the aida committee during its mandate , namely health , the green deal , external policy and security , competitiveness , the future of democracy and the labour market; ### 16. illustrates that the present report addresses six ai case studies in detail , outlining the opportunities offered by ai in the respective sector , the risks to be addressed and the obstacles currently preventing from fully harnessing the benefits of ai; highlights that the case studies represent some of the currently most important ai use cases and , at the same time , reflect some of the main topics of the public hearings held by the aida committee during its mandate , namely health , the green deal , external policy and security , competitiveness , the future of democracy and the labour market;


### 17. stresses that ai can unlock solutions in the health sector that could save millions of lives , improve our standards of living and bring a competitive edge to the european ict sector; ### 17. stresses that ai can unlock solutions in the health sector that could save millions of lives , improve our standards of living and bring a competitive edge to the european ict sector; highlights in this respect the potential of ai-based solutions in reinforcing the resilience and sustainability of eu’s healthcare systems , while offering innovative therapies and better diagnosis using real-world data;


### 17. stresses that ai can unlock solutions in the health sector that could save millions of lives , improve our standards of living and bring a competitive edge to the european ict sector; ### 17. stresses that ai can unlock solutions in the health sector that could enormously speed up scientific research , save millions of lives and improve our quality of life , if the inherent risks are appropriately managed;


### 17. stresses that ai can unlock solutions in the health sector that could save millions of lives , improve our standards of living and bring a competitive edge to the european ict sector; ### 17. stresses that ai can unlock solutions in the health sector that could save millions of life-years and improve quality of life , while at the same time bringing a competitive edge to the european ict sector;


### 18. underlines that ai is already being used to detect diseases and abnormalities at an early stage and more accurately through real-time pattern recognition and image processing , thus speeding up diagnosis and treatment and reducing unnecessary biopsies; ### 18. underlines that ai is already being used to detect diseases and abnormalities at an early stage and more accurately through real-time pattern recognition and image processing , thus speeding up diagnosis and treatment and reducing unnecessary invasive exams; notes , moreover , that ai can enhance personalised medicine and patient care , speed up delivery of care , and help manage population’s health proactively , by empowering citizens and promoting healthy habits and healthier choices;


### 18. underlines that ai is already being used to detect diseases and abnormalities at an early stage and more accurately through real-time pattern recognition and image processing , thus speeding up diagnosis and treatment and reducing unnecessary biopsies; ### 18. underlines that ai is already being experimented with in clinical settings with the aim of preventing and detecting diseases at an early stage and more accurately through , for example , real-time pattern recognition and image processing;


### 19. highlights that ai has the potential to speed up the development of new drugs , treatments and vaccines at a lower cost , while improving the quality and overall safety of the production process; finds that ai can help predict the outcome of and responses to treatments with increasing levels of accuracy when based on high-quality data , thus increasing the effectiveness of preventive care; ### 19. highlights that ai has the potential to speed up the development of new drugs , treatments and vaccines at a lower cost , while improving the quality and overall safety of the production process; finds that ai can help predict the outcome of and responses to treatments with increasing levels of accuracy when based on high-quality data , thus increasing the effectiveness of preventive care; underlines in this respect the importance of ensuring interoperability of hpc with ai as major economic sectors relying on hpc include manufacturing , health and pharmaceuticals;


### 19. highlights that ai has the potential to speed up the development of new drugs , treatments and vaccines at a lower cost , while improving the quality and overall safety of the production process; finds that ai can help predict the outcome of and responses to treatments with increasing levels of accuracy when based on high-quality data , thus increasing the effectiveness of preventive care; ### 19. highlights that ai has the potential to speed up the development of new drugs , treatments and vaccines at a lower cost , while improving the quality and overall safety of the production process; finds that ai can help predict the outcome of and responses to treatments with increasing levels of accuracy when based on high-quality data , thus increasing the effectiveness of preventive care on the condition that all ethical requirements concerning privacy , data protection and informed consent are met;


### 19. highlights that ai has the potential to speed up the development of new drugs , treatments and vaccines at a lower cost , while improving the quality and overall safety of the production process; finds that ai can help predict the outcome of and responses to treatments with increasing levels of accuracy when based on high-quality data , thus increasing the effectiveness of preventive care; ### 19. highlights that ai could hold the potential to speed up the development of new drugs , treatments and vaccines at a lower cost , while improving the quality and overall safety of the production process , but the results so far have proven its limits; finds that ai can help predict the outcome of and responses to treatments with increasing levels of accuracy when based on high-quality data , thus increasing the effectiveness of preventive care;


### 19. highlights that ai has the potential to speed up the development of new drugs , treatments and vaccines at a lower cost , while improving the quality and overall safety of the production process; finds that ai can help predict the outcome of and responses to treatments with increasing levels of accuracy when based on high-quality data , thus increasing the effectiveness of preventive care; ### 19. highlights that ai has the potential to speed up the development of new drugs , treatments and vaccines , and at a lower cost , while improving the quality and overall safety of the production process; finds that ai can help adjust therapeutic strategies according to individual genetic , physiological and social characteristics , if based on high-quality data and sound assumptions;


### 20. underlines that ai has the potential to tailor treatments and drug development to specific patient needs and enhance engagement with stakeholders and participants in the healthcare system; finds that ai and access to datasets increase the potential for healthcare professionals to better understand the patterns and symptoms of their patients and therefore provide better feedback , guidance and support; ### 20. underlines that ai has the potential to tailor treatments and drug development to specific patient needs and enhance engagement with stakeholders and participants in the healthcare system; finds that ai and access to anonymised datasets increase the potential for healthcare professionals to better understand the patterns and symptoms of their patients and therefore provide better feedback , guidance and support; highlights that citizens from all the member states should be able to share their health data with healthcare providers and authorities of their choice; notes that ai must have an assistive role in healthcare , and that professional human oversight should be maintained;


### 20. underlines that ai has the potential to tailor treatments and drug development to specific patient needs and enhance engagement with stakeholders and participants in the healthcare system; finds that ai and access to datasets increase the potential for healthcare professionals to better understand the patterns and symptoms of their patients and therefore provide better feedback , guidance and support; ### 20. underlines that ai has the potential to tailor treatments and drug development to specific patient needs and enhance engagement with stakeholders and participants in the healthcare system; finds that ai and access to datasets increase the potential for healthcare professionals to better understand the patterns and symptoms of their patients and therefore provide better feedback , guidance and support; underlines in this regard the need to create incentives for up-skilling , re-skilling and out-skilling of workers for health care careers;


### 20. underlines that ai has the potential to tailor treatments and drug development to specific patient needs and enhance engagement with stakeholders and participants in the healthcare system; finds that ai and access to datasets increase the potential for healthcare professionals to better understand the patterns and symptoms of their patients and therefore provide better feedback , guidance and support; ### 20. underlines that ai has the potential to tailor treatments and drug development to specific patient needs and enhance engagement with stakeholders and participants in the healthcare system; finds that ai and access to relevant , updated and high-quality datasets , in line with the eu rules on personal data protection , increase the potential for healthcare professionals to better understand the patterns and symptoms of their patients and therefore provide better feedback , guidance and support;


### 20. underlines that ai has the potential to tailor treatments and drug development to specific patient needs and enhance engagement with stakeholders and participants in the healthcare system; finds that ai and access to datasets increase the potential for healthcare professionals to better understand the patterns and symptoms of their patients and therefore provide better feedback , guidance and support; ### 20. finds that ai and access to good quality , representative datasets increase the potential for health professionals to better understand and care for their patients and therefore provide better feedback , guidance and support; highlights that this may be particularly helpful in selecting and reviewing the increasing amounts of scientific knowledge to extract relevant insights for health professionals;


### 21. finds that the fight against covid-19 has both accelerated research into and the deployment of new technologies , notably ai applications , in the quest for improved case detection , and heightened the need for industry and publicly funded research to be able to deploy ai to strengthen the monitoring and modelling of the spread of future pandemics , without excessive limitations on freedom of movement , the infringement of data protection principles or the risk of establishing excessive surveillance regimes; ### deleted


### 21. finds that the fight against covid-19 has both accelerated research into and the deployment of new technologies , notably ai applications , in the quest for improved case detection , and heightened the need for industry and publicly funded research to be able to deploy ai to strengthen the monitoring and modelling of the spread of future pandemics , without excessive limitations on freedom of movement , the infringement of data protection principles or the risk of establishing excessive surveillance regimes; ### 21. finds that the fight against covid-19 has both accelerated research into and the deployment of new technologies , notably ai applications , in the quest for improved case detection , and heightened the need for industry and publicly funded research to be able to deploy ai to strengthen the monitoring and modelling of the spread of future pandemics , without excessive limitations on freedom of movement , the infringement of data protection principles or the risk of establishing excessive surveillance regimes; notes , however , that the experience with the ai applications covid-19 has revealed some of the limitations of the use of ai in medical diagnostics;19b and calls for the ai tools to be used as a support , not as a replacement for human clinical decision making;


### 21. finds that the fight against covid-19 has both accelerated research into and the deployment of new technologies , notably ai applications , in the quest for improved case detection , and heightened the need for industry and publicly funded research to be able to deploy ai to strengthen the monitoring and modelling of the spread of future pandemics , without excessive limitations on freedom of movement , the infringement of data protection principles or the risk of establishing excessive surveillance regimes; ### 21. finds that the fight against covid-19 has both accelerated research into new technologies , notably ai applications , in the quest for improved clinical care and therapeutics research , and highlighted the usefulness of ai to strengthen the monitoring and modelling of the spread of future infectious disease outbreaks , without excessive limitations on freedom of movement , the infringement of data protection principles or the risk of establishing excessive surveillance regimes;


### 22. highlights the potential of ai systems to relieve healthcare systems , and especially medical staff , by supporting routine tasks such as patient transport and reminding patients of their medication , and to remedy challenges posed by rapidly ageing populations; ### 22. highlights the potential of ai systems to relieve healthcare systems , and especially medical staff from the inevitable pressure coming from increasingly ageing populations as well as protect them from dangerous diseases , by supporting routine tasks such as disinfection of facilities , patient transport or by assisting doctors in high-precision diagnostic exams and complex surgeries;


### 22. highlights the potential of ai systems to relieve healthcare systems , and especially medical staff , by supporting routine tasks such as patient transport and reminding patients of their medication , and to remedy challenges posed by rapidly ageing populations; ### 22. highlights the potential of ai systems to relieve health systems , and health professionals , by supporting routine tasks such as patient transportation and monitoring , clinical notetaking , and reminding patients of their medication , as well as by shifting care to maintaining health and preventing disease;


### 23. stresses that consumer health applications based on ai can help to track an individual’s health status , yield data which can apply to early triage questions and encourage healthy behaviour , thus reducing the need to seek advice from a healthcare professional; ### 23. stresses that consumer health applications based on ai can help track an individual’s health status , yield data which can apply to early triage questions and encourage healthy behaviour , thus reducing the need to seek advice from a healthcare professional; points out , however , the particular sensitivity of personal health data and to the risk of data breaches or misuses in this regard;


### 23. stresses that consumer health applications based on ai can help to track an individual’s health status , yield data which can apply to early triage questions and encourage healthy behaviour , thus reducing the need to seek advice from a healthcare professional; ### 23. stresses that consumer health applications based on ai can help to track an individual’s health status , yield data which can apply to early triage questions and encourage healthy behaviour , thus supporting healthcare professionals and equipping patients with additional means to monitor their own health;


### 24. stresses that ai in the health sector is particularly dependent on large amounts of personal data , data sharing , data accessibility and data interoperability to realise the full potential of ai and health , which are currently lacking; stresses the need to combat mistrust and to educate and better inform citizens about the benefits of ai in the field of health; ### 24. stresses that ai in the health sector is particularly dependent on large amounts of personal data , data sharing , data accessibility and data interoperability to realise the full potential of ai and health and welcomes the creation of a european health data space in order to build-in very high quality data to be used in the health sector; believes that ethical requirements will contribute to combat mistrust among citizens , notwithstanding the need to promote an ai illustration that will inform citizens on the benefits and risk of ai , also in the field of health;


### 24. stresses that ai in the health sector is particularly dependent on large amounts of personal data , data sharing , data accessibility and data interoperability to realise the full potential of ai and health , which are currently lacking; stresses the need to combat mistrust and to educate and better inform citizens about the benefits of ai in the field of health; ### 24. stresses that ai in the health sector is particularly dependent on large amounts of personal data , data sharing , data accessibility and data interoperability to realise the full potential of ai and health , which are currently lacking; stresses the need to combat mistrust by introducing binding ethical and legal standards and meaningful rights and redress for people impacted by ai systems and to educate and better inform citizens about the benefits of ai in the field of health as well as ai developers about the challenges and the risks of processing sensitive data in this domain;


### 24. stresses that ai in the health sector is particularly dependent on large amounts of personal data , data sharing , data accessibility and data interoperability to realise the full potential of ai and health , which are currently lacking; stresses the need to combat mistrust and to educate and better inform citizens about the benefits of ai in the field of health; ### 24. stresses that ai in the health sector is particularly dependent on large amounts of personal data , data sharing , data accessibility and data interoperability to realise the full potential of ai and health , which are currently lacking , while putting in place robust ethical requirements; stresses the need to combat mistrust and to educate and better inform citizens about the benefits of ai in the field of health;


### 24. stresses that ai in the health sector is particularly dependent on large amounts of personal data , data sharing , data accessibility and data interoperability to realise the full potential of ai and health , which are currently lacking; stresses the need to combat mistrust and to educate and better inform citizens about the benefits of ai in the field of health; ### 24. stresses that ai in the health sector is particularly dependent on large amounts of personal data , data sharing , data accessibility and data interoperability to realise the full potential of ai and health , which are currently lacking; underlines that the very same data can be used , for example , by insurance companies to price-discriminate;


### 25. stresses that additional legal steps , time and purpose limitations introduced by the gdpr , and differing interpretations across member states have led to legal uncertainty and a lack of cooperation in the health sector; underlines that specific consent obligations hinder the processing of used medical data for further analysis and studies; stresses that this leads to lengthy delays to scientific discoveries and a significant bureaucratic burden in health research20 ; ### deleted


### 25. stresses that additional legal steps , time and purpose limitations introduced by the gdpr , and differing interpretations across member states have led to legal uncertainty and a lack of cooperation in the health sector; underlines that specific consent obligations hinder the processing of used medical data for further analysis and studies; stresses that this leads to lengthy delays to scientific discoveries and a significant bureaucratic burden in health research20 ; ### 25. recognises that the obligations and safeguards introduced by the gdpr , and differing interpretations across member states have changed the way data is shared in the health sector , leading in some cases to lengthy delays in scientific discoveries and bureaucratic burden in health research20; stresses that the creation of a european health data space , in combination with the deployment of blockchain infrastructure and open id that guarantees patients' rights and data portability , can increase cooperation and stimulate data sharing for research and innovation in the european health sector;


### 25. stresses that additional legal steps , time and purpose limitations introduced by the gdpr , and differing interpretations across member states have led to legal uncertainty and a lack of cooperation in the health sector; underlines that specific consent obligations hinder the processing of used medical data for further analysis and studies; stresses that this leads to lengthy delays to scientific discoveries and a significant bureaucratic burden in health research20 ; ### 25. stresses that an efficient and uniform application of the gdpr across the eu is needed to overcome challenges such as legal uncertainty and a lack of cooperation in the health sector; underlines that specific consent obligations hinder the processing of used medical data for further analysis and studies; stresses that this leads to lengthy delays to scientific discoveries and a significant bureaucratic burden in health research20;


### 26. underlines that automatic decision-making in healthcare applications may pose risks to patients’ well-being , although ai already outperforms doctors’ diagnoses in several instances , such as breast cancer21 ; finds that current liability frameworks do not provide sufficient legal certainty over who is accountable in the event of misdiagnosis through ai , for example; ### 26. underlines that automatic decision-making in healthcare applications may pose risks to patients’ well-being and fundamental rights , although ai already outperforms doctors’ diagnoses in several instances , such as breast cancer21; finds that current liability frameworks do not provide sufficient legal certainty over who is accountable in the event of misdiagnosis through ai , for example; notes that ai engineers or the companies employing them should remain accountable for the social , environmental and human health impacts that ai systems or robotics may impose on present and future generations;


### 26. underlines that automatic decision-making in healthcare applications may pose risks to patients’ well-being , although ai already outperforms doctors’ diagnoses in several instances , such as breast cancer21 ; finds that current liability frameworks do not provide sufficient legal certainty over who is accountable in the event of misdiagnosis through ai , for example; ### 26. underlines that automatic decision-making in healthcare applications may pose risks to patients’ well-being; notes that , despite several studies claiming ai is outperforming health professionals in diagnosis21 , there is still a need to confirm those results outside a controlled or a-posteriori test environment; finds that current liability frameworks do not provide sufficient legal certainty over who is accountable in the event of misdiagnosis through ai , for example;


### 26. underlines that automatic decision-making in healthcare applications may pose risks to patients’ well-being , although ai already outperforms doctors’ diagnoses in several instances , such as breast cancer21 ; finds that current liability frameworks do not provide sufficient legal certainty over who is accountable in the event of misdiagnosis through ai , for example; ### 26. underlines that automated decision-making in healthcare applications may pose risks to patients’ well-being; finds that current liability frameworks do not provide sufficient legal certainty over who is accountable in the event of misdiagnosis through ai , for example; welcomes , in this regard , the upcoming legislative proposal on ai liability;


### 104. calls for the creation of an adequately resourced mechanism to supervise the uniform , eu-wide implementation and enforcement of the upcoming ai laws; prefers a european ai board over the creation of a costly new eu agency for ai; suggests , however , that this board should be made up of not only the national ai supervisory authorities and the european data protection board (edpb) , but also a broad range of relevant eu bodies , such as the eu agency for fundamental rights , the high-level expert group on ai , the eu agency for cybersecurity , the european consumer consultative group , and standardisation organisations the european committee for standardization , the european committee for electrotechnical standardization and the european telecommunications standards institute; ### 104. calls for the creation of an independent and adequately resourced mechanism to supervise the uniform , eu-wide implementation and enforcement of the upcoming ai laws; considers that establishing a european agency for ai will be the most suitable , efficient and best cost-effective mechanism , in view of the complexity and the multidisciplinary expertise approach needed for the appropriate implementation of ai laws;


### 104. calls for the creation of an adequately resourced mechanism to supervise the uniform , eu-wide implementation and enforcement of the upcoming ai laws; prefers a european ai board over the creation of a costly new eu agency for ai; suggests , however , that this board should be made up of not only the national ai supervisory authorities and the european data protection board (edpb) , but also a broad range of relevant eu bodies , such as the eu agency for fundamental rights , the high-level expert group on ai , the eu agency for cybersecurity , the european consumer consultative group , and standardisation organisations the european committee for standardization , the european committee for electrotechnical standardization and the european telecommunications standards institute; ### 104. calls for the creation of an adequately resourced mechanism to supervise the uniform , eu-wide implementation and enforcement of the upcoming ai-related legislation; suggests , however , that this body should be made up of not only the national ai supervisory authorities and the european data protection board (edpb) , but also a broad range of relevant eu bodies , such as the eu agency for fundamental rights , the high-level expert group on ai , the eu agency for cybersecurity , the european consumer consultative group , and standardisation organisations the european committee for standardization , the european committee for electrotechnical standardization and the european telecommunications standards institute;


### 104. calls for the creation of an adequately resourced mechanism to supervise the uniform , eu-wide implementation and enforcement of the upcoming ai laws; prefers a european ai board over the creation of a costly new eu agency for ai; suggests , however , that this board should be made up of not only the national ai supervisory authorities and the european data protection board (edpb) , but also a broad range of relevant eu bodies , such as the eu agency for fundamental rights , the high-level expert group on ai , the eu agency for cybersecurity , the european consumer consultative group , and standardisation organisations the european committee for standardization , the european committee for electrotechnical standardization and the european telecommunications standards institute; ### 104. calls for the creation of an adequately resourced mechanism to supervise the uniform , eu-wide implementation and enforcement of the upcoming ai laws; calls for the creation of an ai board , suggests , however , that this board should be made up of not only the national ai supervisory authorities and the european data protection board (edpb) , but also a broad range of relevant eu bodies , such as the eu agency for fundamental rights , the high-level expert group on ai , the eu agency for cybersecurity , the european consumer consultative group , and standardisation organisations the european committee for standardization , the european committee for electrotechnical standardization and the european telecommunications standards institute;


### 105. highlights that the underlying objective of the eu’s digital strategy , as well as that of the ai strategy is to create a ‘european way’ in a digitalised world; clarifies that this approach should be human-centred , value-oriented and based on the concept of the social market economy; underlines that the individual , with their respective dignity and individual freedoms , should always remain at the centre of all political considerations; ### 105. highlights that the underlying objective of the eu’s digital strategy , as well as that of the ai strategy is to create a ‘european way’ in a digitalised world; clarifies that this approach should be human-centred , value-oriented and based on a respect for fundamental rights and on the concept of the social market economy; underlines that the individual , with their respective dignity and individual freedoms , should always remain at the centre of all political considerations;


### 105. highlights that the underlying objective of the eu’s digital strategy , as well as that of the ai strategy is to create a ‘european way’ in a digitalised world; clarifies that this approach should be human-centred , value-oriented and based on the concept of the social market economy; underlines that the individual , with their respective dignity and individual freedoms , should always remain at the centre of all political considerations; ### 105. highlights that the underlying objective of the eu’s digital strategy , as well as that of the ai strategy is to create a ‘european way’ in a digitalised world; clarifies that this approach should be human-centric , value-oriented , trustworthy and based on the concept of the social market economy; underlines that citizens , with their fundamental rights and freedoms , should always remain at the centre of all political and legislative considerations;


### 106. agrees with the conclusion drawn by the commission in its 2020 white paper on artificial intelligence that there is a need to establish a risk-based legal framework for ai , covering high-level ethical standards combined with appropriate liability rules and sector-specific provisions , while at the same time providing the private sector with enough flexibility , practicability and legal certainty to develop new business models based on ai technologies; ### 106. agrees with the conclusion drawn by the commission in its 2020 white paper on artificial intelligence that there is a need to establish a risk-based legal framework for ai , covering high-level ethical standards and product safety provisions combined with appropriate liability rules and sector-specific provisions , while at the same time providing businesses with enough legal certainty and a level playing field to foster ai uptake and innovation based on eu values;


### 107. states that the co-legislators should aim to align the ai definition in future legislation with the concepts , terminologies and standards developed together with other like-minded democratic countries in the oecd44 ; stresses that doing so would give the eu an advantage in shaping a future international ai governance system; ### deleted


### 108. is convinced that it is not ai as a technology that should be regulated , but that the type , intensity and timing of regulatory intervention should solely depend on the type of risk incurred by the use of an ai system; underlines , in this regard , the importance of distinguishing between a minority of ‘high-risk’ and the vast majority of ‘low-risk’ ai use cases; concludes that while only the former category indeed demands legislative safeguards , businesses should self-regulate ‘low-risk’ technologies by choosing measures that deliver the best outcomes; ### deleted


### 108. is convinced that it is not ai as a technology that should be regulated , but that the type , intensity and timing of regulatory intervention should solely depend on the type of risk incurred by the use of an ai system; underlines , in this regard , the importance of distinguishing between a minority of ‘high-risk’ and the vast majority of ‘low-risk’ ai use cases; concludes that while only the former category indeed demands legislative safeguards , businesses should self-regulate ‘low-risk’ technologies by choosing measures that deliver the best outcomes; ### 108. is convinced that it is not ai as a technology that should be regulated , but that the type , intensity and timing of regulatory intervention should solely depend on the type of individual and/or societal risk incurred by the use of an ai system; underlines , in this regard , the importance of distinguishing between a gradually increasing number of ‘high-risk’ and the vast majority of ‘low-risk’ ai use cases; concludes that while only the former category indeed demands strict legislative safeguards , businesses should self-regulate ‘low-risk’ technologies by choosing measures that deliver the best outcomes and which should be monitored and audited if needed by public authorities. believes that artificial intelligence systems , especially those with built-in autonomy , including the capability to independently extract , collect , and share sensitive information with various stakeholders , and the possibility of self-learning or even evolving to self-modify , should be subject to robust conceptual laws and principles. stresses that ai systems must not keep or disclose personal confidential information without explicit approval from the source of that information;


### 109. specifies that the classification of technologies as ‘high-risk’ should be based on the concrete use and context , complexity and autonomy of the ai system , the probability and likelihood of the worst-case scenario , the severity of the harm and its irreversibility , the techniques used and the governance arrangements adopted; stresses that this classification should be introduced together with best practices and guidance for ai developers and should also recognise that ai technologies can significantly reduce certain risks; ### deleted


### 109. specifies that the classification of technologies as ‘high-risk’ should be based on the concrete use and context , complexity and autonomy of the ai system , the probability and likelihood of the worst-case scenario , the severity of the harm and its irreversibility , the techniques used and the governance arrangements adopted; stresses that this classification should be introduced together with best practices and guidance for ai developers and should also recognise that ai technologies can significantly reduce certain risks; ### 109. specifies that the classification of technologies as ‘high-risk’ should be based on the concrete use and context , complexity and autonomy of the ai system , the probability and likelihood of the worst-case scenario , the severity of the harm , the degree of moral hazard and its irreversibility , the techniques used and the governance arrangements adopted; stresses that this classification should be introduced together with best practices and guidance for ai developers and should also recognise that ai technologies can significantly reduce certain risks; stresses that the right to privacy must always be respected. an ai developer should guarantee that individuals are not personally identifiable , aside from exceptional circumstances and then only with clear , unambiguous informed consent. human informed consent should be pursued and obtained prior to any man-machine interaction. as such , ai designers have a responsibility to develop and follow procedures for valid consent , confidentiality , anonymity , fair treatment and due process. designers will comply with any requests that any related data be destroyed , and removed from any datasets;


### 110. notes that the requirements that ai systems need to fulfil differ significantly in a business-to-business (b2b) environment compared to a business-to-consumer (b2c) environment; points out that while consumer rights need to be legally protected through consumer protection legislation , companies can solve liability and other legal challenges more quickly and cost-effectively by contractual means with business partners directly; concludes that , in particular , smes and start-ups investing in ai technologies would benefit from a b2b exclusion as they are disproportionately affected by new legal obligations , which also harms their ability to attract investments; ### deleted


### 111. underlines the need to address open ethical questions raised by new technological possibilities , but clarifies that new ai ethical guidelines should not set up stricter rules than those already existing for human or automated actions; proposes that on these grounds the eu should introduce ethical guidelines that consist of three categories of core values and principles; ### deleted


### 112. explains that the first category could list fundamental , mandatory principles such as the non-maleficence principle , the principle of respecting human dignity or the protection of the democratic process; states that the second category could include good practices in ai development such as human-centric ai , responsible governance and the principles of transparency and explainability; concludes that the last category could include principles of sustainable ai that would be fully aligned with the un 2030 agenda for sustainable development; ### deleted


### 113. highlights , with regard to the third category , the gap in leadership on ai global governance , which gives the eu the chance to become the leading voice in aligning ai with the un sdgs and using ai technologies to push worldwide for their achievement; stresses , however , that not all ai technologies developed or applied in the eu should need to comply with all three categories; suggests , for example , that sustainable ai could only be mandated for ai implemented or procured by public tender or in specific sectors , while the majority of ai developers and companies would only be encouraged to align with the second and third categories through soft law; ### deleted


### 113. highlights , with regard to the third category , the gap in leadership on ai global governance , which gives the eu the chance to become the leading voice in aligning ai with the un sdgs and using ai technologies to push worldwide for their achievement; stresses , however , that not all ai technologies developed or applied in the eu should need to comply with all three categories; suggests , for example , that sustainable ai could only be mandated for ai implemented or procured by public tender or in specific sectors , while the majority of ai developers and companies would only be encouraged to align with the second and third categories through soft law; ### 113. highlights , with regard to the third category , the gap in leadership on ai global governance , which gives the eu the chance to become the leading voice in aligning ai with the un sdgs and the fundamental rights legal acquis , and using ai technologies to push worldwide for their achievement; stresses , however , that not all ai technologies developed or applied in the eu should need to comply with all three categories; suggests , for example , that sustainable ai could only be mandated for ai implemented or procured by public tender or in specific sectors , while the majority of ai developers and companies would only be encouraged to align with the second and third categories through soft law;


### 114. is convinced that efforts to completely ‘de-bias’ ai algorithms are frequently misguided , because this strategy wrongly suggests that bias-free data sets exist; notes that in this regard the requirement that data used to train ai systems is ‘complete and free of errors’ needs to be revisited; stresses , however , that the eu should at the same time cooperate very closely with ai developers to counterbalance structural biases in our societies and daily life; ### deleted


### 114. is convinced that efforts to completely ‘de-bias’ ai algorithms are frequently misguided , because this strategy wrongly suggests that bias-free data sets exist; notes that in this regard the requirement that data used to train ai systems is ‘complete and free of errors’ needs to be revisited; stresses , however , that the eu should at the same time cooperate very closely with ai developers to counterbalance structural biases in our societies and daily life; ### 114. is convinced that efforts to completely ‘de-bias’ ai algorithms are frequently misguided , because this strategy wrongly suggests that bias-free data sets exist; notes that in this regard the requirement that data used to train ai systems is ‘complete and free of errors’ needs to be balanced , as done in the upcoming draft for ai act44a; stresses , that the eu should cooperate very closely with ai developers to counterbalance structural biases in our societies and daily life;


### 115. elaborates that transparency or explainability obligations for ai systems , while helpful in certain cases , may not be possible to implement in every instance; notes that both concepts also need to be balanced against other factors , including the interests of businesses in maintaining trade secrets or the potential value of exposed data to potential competitors; stresses , however , that a mandatory self-identification of ai systems or accessible machine logs seem to be very useful for many ai use cases that interfere with the fundamental rights of individuals or affect consumers; ### deleted


### 116. states that the legislative framework on intellectual property must continue to incentivise and protect ai innovators by granting them patents as a reward for developing and publishing their creations; finds that existing laws are mostly future-proof , but proposes certain adjustments , including the integration of open source elements and new forms of patent licensing to ensure that tools are available to regions and initiatives that could not otherwise afford them; recognises that it will also be necessary to clarify whether ai will be able to hold intellectual property rights in itself; ### 116. states that the legislative framework on intellectual property must continue to incentivise and protect ai innovators by granting them patents as a reward for developing and publishing their creations; finds that existing laws are mostly future-proof , but proposes certain adjustments , including the integration of open source and open standards as well as new forms of patent licensing to ensure that tools are available to regions and initiatives that could not otherwise afford them; recommends publicly funded ai-research projects to be open source/open standards;


### 116. states that the legislative framework on intellectual property must continue to incentivise and protect ai innovators by granting them patents as a reward for developing and publishing their creations; finds that existing laws are mostly future-proof , but proposes certain adjustments , including the integration of open source elements and new forms of patent licensing to ensure that tools are available to regions and initiatives that could not otherwise afford them; recognises that it will also be necessary to clarify whether ai will be able to hold intellectual property rights in itself; ### 116. states that the legislative framework on intellectual property must continue to incentivise and protect ai innovators by granting them patents as a reward for developing and publishing their creations; finds that existing laws are mostly future-proof , but proposes certain adjustments , including the integration of open source elements , the use of public procurement to encourage open source ai digital solutions in the public and private sector , and new forms of patent licensing to ensure that tools are available to regions and initiatives that could not otherwise afford them; recognises that it will also be necessary to clarify whether ai will be able to hold intellectual property rights in itself;


### 116. states that the legislative framework on intellectual property must continue to incentivise and protect ai innovators by granting them patents as a reward for developing and publishing their creations; finds that existing laws are mostly future-proof , but proposes certain adjustments , including the integration of open source elements and new forms of patent licensing to ensure that tools are available to regions and initiatives that could not otherwise afford them; recognises that it will also be necessary to clarify whether ai will be able to hold intellectual property rights in itself; ### 116. states that the legislative framework on intellectual property must continue to incentivise and protect ai innovators by granting them patents as a reward for developing and publishing their creations; finds that existing laws are mostly future-proof , but proposes certain adjustments , including the integration of open source elements and new forms of patent licensing to ensure that tools are available to regions and initiatives that could not otherwise afford them; is of the opinion that ai itself should not be entitled intellectual property rights for entirely ai-made creations , nor should their owners , in order to avoid market distortions to the expense of human creators;


### 117. elaborates that obligatory ex ante risk self-assessments , comparable with ce markings or data protection impact assessments , combined with market surveillance based on clear rules and standards , and complemented with ex post enforcement for high-risk ai systems , seem to be a sufficiently robust governance approach for ai; warns that overly burdensome conformity assessment obligations could create significant burdens that make the business models of ai developers and companies economically unviable; ### deleted


### 118. notes that in order to increase product safety and improve the identification of faults , the developers of high-risk ai should at least be obliged to ensure that accessible logs of algorithmic activity are maintained securely; considers that developers should also design high-risk ai systems with embedded mechanisms – ‘kill switches’ – for human intervention to immediately halt automated activities at any moment; ### deleted


### 118. notes that in order to increase product safety and improve the identification of faults , the developers of high-risk ai should at least be obliged to ensure that accessible logs of algorithmic activity are maintained securely; considers that developers should also design high-risk ai systems with embedded mechanisms – ‘kill switches’ – for human intervention to immediately halt automated activities at any moment; ### 118. notes that in order to increase product safety and improve the identification of faults , the developers of high-risk ai should at least be obliged to ensure that accessible logs of algorithmic activity are maintained securely; considers that developers should also design high-risk ai systems with embedded mechanisms – ‘kill switches’ – for human intervention to immediately halt automated activities at any moment and ensure a human-in-the-loop approach; considers that it should always be possible to reduce the ai system´s computations to a form comprehensible by humans; suggests that ai products be equipped with a ‘black box’ which records data on every transaction carried out by the ai-system , including the logic that contributed to each of its decisions;


### 119. is convinced that despite the legal challenges caused by ai systems , there is no need for a complete revision of the existing liability rules; stresses that the product liability directive and the national fault-based liability regimes can in principle remain the centrepiece legislation for countering most harm caused by ai; underlines that only in some cases could there be inappropriate outcomes , but warns that any revision should take the existing product safety legislation into account and should solely be based on clearly identified gaps; ### 119. is convinced that the intrinsic characteristics of ai and its ability to adapt call for a specific liability regime and looks forward in this regard to the presentation of the commission’s legislative proposal on ai liability;


### 120. notes that certain changes to the legal definitions of ‘product’ , including integrated software applications , digital services and inter-product dependency , and ‘producer’ , including backend operator , service provider and data supplier , do however seem necessary to ensure that compensation is available for harm caused by emerging technologies; stresses , however , that an overly broad approach to the definition of ‘product’ should be avoided , as this may make it difficult to differentiate between ai and other algorithms; ### deleted


### 121. points out that , due to the characteristics of ai systems , such as their autonomy and opacity , there could also be cases where neither an updated product liability directive nor national fault-based liability regimes apply and where persons who suffer harm or whose property is damaged would end up without compensation; suggests , therefore , the introduction of a limited new liability mechanism for legal claims against the operator , who controls the risks associated with the ai system and who also often is the cheapest cost avoider; specifies that while high-risk ai systems should fall under strict liability , combined with mandatory insurance cover , victims of low-risk ai systems should only benefit from a presumption of fault against the operator; ### deleted


### 122. agrees with the conclusion drawn by the commission in its 2020 communication entitled ‘a european strategy for data’ that the creation of a single european data space is key to ensuring the eu’s global competitiveness in ai , as well as its strategic sovereignty and economic prosperity; recalls the essential link between the availability of high-quality data and the development of ai; ### 122. agrees with the conclusions drawn by the commission in its 2020 communication entitled ‘a european strategy for data’ and by the european parliament on its resolution on the european strategy for data , that the creation of a single european data space is key to ensuring the eu’s global competitiveness in ai , as well as its strategic sovereignty and economic prosperity; recalls the essential link between the availability of high-quality data and the development of ai; and calls for the consistent and harmonized regulatory framework in european competition policy , data regulation and privacy rules for the use and access of data;


### 122. agrees with the conclusion drawn by the commission in its 2020 communication entitled ‘a european strategy for data’ that the creation of a single european data space is key to ensuring the eu’s global competitiveness in ai , as well as its strategic sovereignty and economic prosperity; recalls the essential link between the availability of high-quality data and the development of ai; ### 122. agrees with the conclusion drawn by the commission in its 2020 communication entitled ‘a european strategy for data’ that the creation of a single european data space is key to ensuring the eu’s global competitiveness in ai , as well as its strategic sovereignty and economic prosperity; recalls the essential link between the availability of high-quality data and the development of ai applications;


### 124. urges the commission to continue its work on removing key barriers for developers and companies in areas such as country-based discrimination , burdensome market access procedures and high regulatory costs , as well as to address the frequent use of derogations which results in diverging rules among different member state jurisdictions; ### 124. urges the commission to continue its work on removing key unjustified barriers preventing the full completion of the digital single market in areas such as country-based discrimination , incomplete mutual recognition of professional qualifications , unjustified burdensome market access procedures and high regulatory costs , as well as to address the frequent use of derogations which results in diverging rules among different member state jurisdictions;


### 125. is convinced that the current national and european competition and antitrust frameworks need to be reformed in order to better target abuses of market power and algorithmic collusion in the digital economy , as well as to better address the risks of new emerging monopolies without compromising innovation; ### 125. is convinced that the current national and european competition and antitrust frameworks need to be reformed in order to better target abuses of market power and algorithmic collusion in the digital economy , as well as to better address the risks of new emerging monopolies without compromising innovation; and calls for specific considerations of potential competition issues in the field of artificial intelligence , in line with the general review of commission’s competition rules to be fit for the digital age44b;


### 125. is convinced that the current national and european competition and antitrust frameworks need to be reformed in order to better target abuses of market power and algorithmic collusion in the digital economy , as well as to better address the risks of new emerging monopolies without compromising innovation; ### 125. is convinced that the current national and european competition and antitrust frameworks need to be reformed in order to better target abuses of market power and algorithmic collusion in the digital economy , as well as to better address the risks of new emerging monopolies without compromising innovation; welcomes in this regard the upcoming approval of the digital markets act;


### 125. is convinced that the current national and european competition and antitrust frameworks need to be reformed in order to better target abuses of market power and algorithmic collusion in the digital economy , as well as to better address the risks of new emerging monopolies without compromising innovation; ### 125. is convinced that the current national and european competition and antitrust frameworks need to be reformed in order to better target abuses of market power and algorithmic collusion in the digital economy , such as related to data accumulation , as well as to better address the risks of new emerging monopolies without compromising innovation;


### 127. stresses that the shift in the volume and processing of data for ai requires the development and deployment of new data processing technologies encompassing the edge , thereby moving away from centralised cloud-based infrastructure models towards increasing decentralisation of data processing capacities; urges the strengthening of european intense-computing ai architectures as a key strategic priority to maximise investment and research , including distributed clusters , the deployment of edge nodes , digital microcontroller initiatives , and the capacity to enable faster data collection and processing in all aspects of society; ### 127. stresses that the shift in the volume and processing of data for ai requires the development and deployment of new data processing technologies encompassing the edge , thereby moving away from centralised cloud-based infrastructure models towards increasing decentralisation of data processing capacities; urges the strengthening of european intense-computing ai-enabling architectures as a key strategic priority to maximise investment and research , including distributed clusters , the deployment of edge nodes , digital microcontroller initiatives;


### 128. stresses that ai requires powerful hardware to make sophisticated algorithms useable , including high-performance and quantum computing and the iot; urges the maximisation of funding and research for such ai-enabled emerging technologies; finds that , similarly , nano-technologies and chips are essential to enabling ai to be embedded in , for example , medical devices , which also requires priority funding; ### 128. stresses that ai requires powerful hardware to make sophisticated algorithms useable , including high-performance and quantum computing and the iot; urges the maximisation of funding and research for such ai-enabled emerging technologies; finds that , similarly , nano-technologies and chips are essential to enabling ai to be embedded in , for example , medical devices; is concerned about the global crisis of microprocessors and welcomes in this regard the commission’s proposal for a “chips act” to shorten supply chains and reduce eu’s current total dependence on external suppliers;


### 129. highlights that a functioning and fast infrastructure for ai must be based on a fair , safe and high-quality foundation by avoiding gaps in digital high-speed connectivity , which requires 5g roll-out in all urban areas by 2030 , as well as ultra-fast broadband networks and spectrum policy with licence conditions that do not distort competition; urges member states to continue to implement the 5g toolbox , specifically enabling legislation related to the risk assessment of suppliers and service providers; calls for the broadband cost reduction directive to be put into practice to facilitate network deployment; ### 129. highlights that a functioning and fast infrastructure for ai must be based on a fair , safe and high-quality foundation by avoiding gaps in digital high-speed connectivity , which requires 5g roll-out in all urban areas by 2030 , as well as ultra-fast broadband networks and spectrum policy; urges member states to continue to implement the 5g toolbox , specifically enabling legislation related to the risk assessment of suppliers and service providers; calls for the broadband cost reduction directive to be put into practice to facilitate network deployment;


### 130. calls on the commission to establish timetables and financial incentives for member states , cities , regions and industry , and to accelerate the administrative approval processes for 5g; supports the incentivisation of private investment in 5g roll-out; requests that in regions where roll-out is not carried out by the private sector , more funds are made available; calls for funding for broadband and connectivity projects under the multiannual financial framework , with easier access for local authorities to avoid the underutilisation of public funds; ### 130. calls on the commission to establish timetables and financial incentives for member states , cities , regions and industry , and to accelerate the administrative approval processes for 5g;


### 131. calls on the commission to establish a precise strategy with a clear timetable for 6g roll-out to better prepare for the next wave of digital infrastructure , enabling europe to take the lead; ### deleted


### 132. finds that it will not be possible to achieve the necessary deployment of dense edge-node connectivity for 5g in rural areas , where half of european households are not even connected through fibre; calls for a clear strategy on fibre-optic network deployment and broadband roll-out in rural areas , which is also key for data intensive technologies such as ai; recommends that european investment bank support for connectivity projects in rural areas be enhanced; ### 132. calls for a clear strategy on fibre-optic network deployment and broadband roll-out in rural areas , which is also key for data intensive technologies such as ai; calls in this regard for increased support by the european investment bank for connectivity projects in rural areas;


### 133. stresses that the significant investment required for network deployment , coupled with the ambitious expectations of public authorities and consumers regarding roll-out timing and coverage , will be impossible to achieve without infrastructure-sharing agreements , which are also key to promoting sustainability and reducing energy consumption; ### 133. stresses that the significant investment required for network deployment , and the swift rollout that would be needed to achieve the ambitious targets set by the digital compass will be impossible to achieve without infrastructure-sharing agreements , which are also key to promoting sustainability and reducing energy consumption;


### 134. urges the eu to take the lead in making green digital infrastructure climate neutral and energy efficient by 2030; calls for coordinated global multilateral action to use ai in the fight against climate change and environmental degradation; ### 134. urges the eu to take the lead in making green digital infrastructure climate neutral and energy efficient by 2030; underlines that the ai transformation should be integrated with the european green deal policy program; calls for coordinated global multilateral action to use ai in the fight against climate change and environmental degradation;


### 134. urges the eu to take the lead in making green digital infrastructure climate neutral and energy efficient by 2030; calls for coordinated global multilateral action to use ai in the fight against climate change and environmental degradation; ### 134. urges the eu to take the lead in making green digital infrastructure climate neutral and energy efficient by 2030;


### 135. calls on the commission to create an ai competence framework for individuals that builds on the digital competence framework for citizens , which helps individuals and smes to find relevant ai training and learning opportunities and to improve the sharing of knowledge , best practices , digital skills initiatives and funding between organisations and companies , at both eu and national level; recommends the establishment of a central body for the european ai skills data space to coordinate european skills training on sectoral and regional levels in all member states; urges the commission and the member states to support free online courses that enhance digital literacy such as basic training in ai; ### 135. calls on the commission to create an ai illustration framework for individuals , building on the digital competence framework for citizens , providing citizens and smes with relevant ai training and learning opportunities and improving the sharing of knowledge , best practices , digital skills initiatives , media and data literacy and funding between organisations and companies , at both eu and national level; recommends that the eu agency for artificial intelligence promote european ai literacy programmes on sectoral and regional levels in all member states; urges member states to support the establishment and promotion of free online courses that enhance digital literacy such as basic training in ai;


### 135. calls on the commission to create an ai competence framework for individuals that builds on the digital competence framework for citizens , which helps individuals and smes to find relevant ai training and learning opportunities and to improve the sharing of knowledge , best practices , digital skills initiatives and funding between organisations and companies , at both eu and national level; recommends the establishment of a central body for the european ai skills data space to coordinate european skills training on sectoral and regional levels in all member states; urges the commission and the member states to support free online courses that enhance digital literacy such as basic training in ai; ### 135. calls on the commission to create an ai competence framework for individuals that builds on the digital competence framework for citizens , which helps organisations , managers , employees , individuals and smes to find relevant ai training and learning opportunities and to improve the sharing of knowledge , best practices , digital skills initiatives and funding between organisations and companies , at both eu and national level; advises the commission to build the competence framework quickly by using existing ai education schemes that are already widely available and accessible; recommends the establishment of a central body for the european ai skills data space to coordinate european skills training on sectoral and regional levels in all member states; urges the commission and the member states to support free online courses that enhance digital literacy such as basic training in ai;


### 135. calls on the commission to create an ai competence framework for individuals that builds on the digital competence framework for citizens , which helps individuals and smes to find relevant ai training and learning opportunities and to improve the sharing of knowledge , best practices , digital skills initiatives and funding between organisations and companies , at both eu and national level; recommends the establishment of a central body for the european ai skills data space to coordinate european skills training on sectoral and regional levels in all member states; urges the commission and the member states to support free online courses that enhance digital literacy such as basic training in ai; ### 135. calls on the commission to create an ai skills framework for individuals , building on the digital competence framework for citizens , providing citizens and smes with relevant ai training and learning opportunities and to improve the sharing of knowledge , best practices , digital skills initiatives and funding between organisations and companies , at both eu and national level; recommends to monitor the creation of quality jobs linked to ai in the eu; urges the commission and the member states to support the establishment and promotion of free online courses that enhance digital literacy such as basic training in ai;


### 136. calls for the eu to increase investment in research into key technologies such as ai , robotics , quantum computing , microelectronics , batteries , the internet of things , nano-technology , distributed ledger technology and 3d printing; calls on the commission to develop and maintain a european strategic research roadmap for ai which includes major interdisciplinary challenges where ai can be a part of the solution; ### 136. calls for the eu to increase investment in research into key technologies such as ai , robotics , quantum computing , microelectronics , batteries , the internet of things , nano-technology , distributed ledger technology and 3d printing; calls on the commission to develop and maintain a european strategic research roadmap for ai which includes major interdisciplinary challenges where ai can be a part of the solution; underlines that especially public investment efforts should be directed to use cases that are likely to increase sustainable solutions in society , increase wellbeing and inclusion in society’;


### 136. calls for the eu to increase investment in research into key technologies such as ai , robotics , quantum computing , microelectronics , batteries , the internet of things , nano-technology , distributed ledger technology and 3d printing; calls on the commission to develop and maintain a european strategic research roadmap for ai which includes major interdisciplinary challenges where ai can be a part of the solution; ### 136. calls for the eu to increase investment in research into key technologies such as ai , robotics , quantum computing , microelectronics , the internet of things and nano-technology; calls on the commission to develop and maintain a european strategic research roadmap for ai which includes major interdisciplinary challenges where it can be a part of the solution;


### 137. encourages all member states to spend a significant proportion of their gdp on research into digital technologies , and for annual combined public and private investments in the eu to reach at least eur 20-25 billion; urges the continued strengthening of the horizon europe programme , notably its ai , data and robotics partnership and the european innovation council , and to expand the digital europe programme , whose allocated funding of eur 7.6 billion46 is insufficient to remain competitive; ### 137. encourages all member states to spend a higher proportion of their gdp on research on digital technologies , and for annual combined public and private investments in the eu to reach at least eur 20-25 billion; urges the continued strengthening of the horizon europe programme , notably its ai , data and robotics partnership and the european innovation council , and to expand the digital europe programme , whose allocated funding of eur 7.6 billion46 is insufficient to remain competitive;


### 138. calls on the commission to simplify and streamline the structure of research funding instruments by reducing the effort and time needed to obtain decisions when applying for grants; stresses the need to improve the quality and consistency of proposal reviews and to increase the predictability of funding instruments and their timing to support long-term planning , using the european ai research roadmap; ### 138. calls on the commission to streamline the structure of research funding instruments by streamlining grant application requirements and processes; stresses the need to improve the quality and consistency of proposal reviews and to increase the predictability of funding instruments and their timing to support long-term planning , using the european ai research roadmap;


### 139. encourages the creation of more chairs on ai at european universities as well as competitive salaries for ai research and the provision of more funding in order to properly train and retain the next generation of researchers and entrepreneurs and prevent brain drain to locations outside the eu; stresses the need to reduce the bureaucratic burden for university researchers in accessing funds and calls on the commission to provide tools to increase digital interconnectivity between universities; urges the development of cross-cutting networks for ai across european universities and research institutions; ### 139. encourages the increase of specific ai curricula at european universities and to support ai research , also considering the need to properly train and retain the next generation of researchers and talent and prevent brain drain to locations outside the eu; stresses the need to reduce the bureaucratic burden for university researchers in accessing funds and calls on the commission to provide tools to increase digital interconnectivity between universities; urges the development of cross-cutting networks for ai across european universities and research institutions;


### 27. highlights that ai applications can bring environmental and economic benefits and strengthen predictive capabilities that contribute to the fight against climate change , to meeting the sustainable development goals (sdgs) and to achieving our target of becoming the first climate-neutral continent; finds that the use of ai has the potential to reduce global greenhouse gas emissions by up to 4 % by 203022 ; underlines that ai systems themselves need to be designed sustainably to reduce resource usage and energy consumption , thereby limiting the risks to the environment; finds that it has been estimated that ict technologies are capable of reducing 10 times more greenhouse gas emissions than their own footprint23 ; ### 27. highlights that ai applications can bring environmental and economic benefits and strengthen predictive capabilities that can contribute to the fight against climate change , and to achieving the eu’s target of becoming the first climate-neutral continent by2050; finds that the use of ai has the potential to reduce global green house gas emissions by up to 4 % by 2030; underlines that ai systems themselves need to be designed sustainably to reduce resource usage and energy consumption , thereby limiting the risks to the environment; finds that according to some estimates , ict technologies are capable of reducing 10times more greenhouse gas emissions than their own footprint; warns , at the same time , that opposing estimates exist , showing that the increasing energy consumption by data storage for the large datasets needed to train ai systems can also have a negative effect that currently overrides the potentially beneficial impact of ai on the environment; adds that the intensive use of raw materials to build microprocessors and high-tech devices using ai can also add to this negative impact;


### 27. highlights that ai applications can bring environmental and economic benefits and strengthen predictive capabilities that contribute to the fight against climate change , to meeting the sustainable development goals (sdgs) and to achieving our target of becoming the first climate-neutral continent; finds that the use of ai has the potential to reduce global greenhouse gas emissions by up to 4 % by 203022 ; underlines that ai systems themselves need to be designed sustainably to reduce resource usage and energy consumption , thereby limiting the risks to the environment; finds that it has been estimated that ict technologies are capable of reducing 10 times more greenhouse gas emissions than their own footprint23 ; ### 27. highlights that ai applications can bring environmental and economic benefits and strengthen predictive capabilities that contribute to the fight against climate change , to meeting the sustainable development goals (sdgs) and to achieving our target of becoming the first climate-neutral continent; finds that the use of ai has the potential to reduce global greenhouse gas emissions by up to 4 % by 203022 ; underlines that in order to guarantee the ‘large handprint but small footprint’ of ai on the environment and climate , ai systems themselves need to be designed sustainably to reduce resource usage and energy consumption , thereby limiting the damage to the environment; finds that it has been estimated that ict technologies may reduce 10 times more greenhouse gas emissions than their own footprint but recognizes that this requires conscious design choices and regulative actions23;


### 27. highlights that ai applications can bring environmental and economic benefits and strengthen predictive capabilities that contribute to the fight against climate change , to meeting the sustainable development goals (sdgs) and to achieving our target of becoming the first climate-neutral continent; finds that the use of ai has the potential to reduce global greenhouse gas emissions by up to 4 % by 203022 ; underlines that ai systems themselves need to be designed sustainably to reduce resource usage and energy consumption , thereby limiting the risks to the environment; finds that it has been estimated that ict technologies are capable of reducing 10 times more greenhouse gas emissions than their own footprint23 ; ### 27. highlights that ai applications can bring environmental and economic benefits and strengthen predictive capabilities that contribute to the fight against climate change , to meeting the sustainable development goals (sdgs) and to achieving our target of becoming the first climate-neutral continent; finds that the use of ai has the potential to reduce global greenhouse gas emissions by up to 4 % by 203022 ; underlines that ai systems themselves need to be designed sustainably to promote sustainable consumption , reduce resource usage and energy consumption , thereby limiting the risks to the environment; finds that it has been estimated that ict technologies are capable of reducing 10 times more greenhouse gas emissions than their own footprint23;


### 28. is concerned that only six member states have included a strong focus on ai applications in their efforts to meet the green deal objectives; finds that ai will produce information relevant to environmental planning , decision-making and the management and monitoring of the progress of environmental policies , for instance for cleaner air , where ai applications can monitor pollution and warn of hazards; highlights that ai and digital solutions have the potential to scale up resource-efficient solutions that would otherwise only be implemented in one company or sector; ### 28. is concerned that only six member states have included a strong focus on ai applications in their efforts to meet the green deal objectives; finds that ai can produce information relevant to environmental planning , decision-making and the management and monitoring of the progress of environmental policies , for instance for cleaner air , where ai applications can monitor pollution and warn of hazards; highlights that ai and digital solutions have the potential to scale up resource-efficient solutions that would otherwise only be implemented in one company or sector;


### 29. emphasises the importance of ai in developing smart cities and smart villages to improve the technological resilience of infrastructures , building on local strengths and opportunities , including public transport , emergency assistance , waste management , urban planning , smart energy and resource optimisation; stresses that ai-based solutions can further assist in optimising architecture , construction and engineering processes to reduce emissions , construction time , costs and waste; finds that this is already a reality in countries such as china and malaysia , where large-scale urban ai systems manage the transport , energy and safety systems of several cities; ### 29. emphasises the importance of ai in developing smart cities and smart villages to improve the technological resilience of infrastructures , building on local strengths and opportunities , including public transport , traffic prediction and reduction , emergency assistance , waste management , urban planning , smart energy and resource optimisation , as is already the case in several cities and municipalities across the eu; stresses that ai-based solutions can further assist in optimising architecture , construction and engineering processes to reduce emissions , construction time , costs and waste;


### 30. stresses that the energy transition will not take place without digitalisation , which will be achieved to a significant extent through ai; underlines that ai can monitor , optimise and reduce energy consumption and production , as well as support the integration of renewable energies into existing electricity grids; ### 30. stresses that the energy transition will not take place without digitalisation , which will be achieved to a significant extent through ai , which can also have a negative impact , given its very high energy consumption;


### 31. highlights that the growing complexity of an energy transition system , with increased volatile renewable generation and changes in load management , makes increasing automated control necessary for energy supply security; stresses that ai benefits for supply security , especially in the operation , monitoring , maintenance and control of water , gas and electricity networks , must be taken into account in the regulation of these networks; ### 31. highlights that the growing complexity of an energy transition system , with increased volatile renewable generation and changes in load management , makes increasing automated control necessary for energy supply security; stresses that ai benefits for security of supply , especially in the operation , monitoring , maintenance and control of water , gas and electricity networks , must be taken into account in the regulation of these networks; stresses however that the use of ai and digital tools to manage critical infrastructures enhances their vulnerabilities without appropriate cybersecurity provisions;


### 32. finds that ai and other digital solutions for mobility and transport have the potential to reduce traffic flows and enhance road safety , by greatly increasing the efficiency of access to transport systems through , for example , autonomous vehicles and optimised public transport planning , thus reducing the environmental footprint of the transport sector , travel times and costs; ### 32. finds that ai and other digital solutions for mobility and transport have the potential to reduce traffic flows and enhance road safety , by greatly increasing the efficiency of transport systems through , for example , optimised public transport planning , thus reducing the environmental footprint of the transport sector , travel times and costs;


### 33. believes that ai can have a transformative role in the agricultural sector when it comes to tackling food security issues , enabling the emergence of new harvesting methods and harvest prediction , novel approaches to food processing and retail , agricultural resource management and input efficiency , as well as improved land management and the optimisation of food supply chains; stresses that agriculture is a key sector in which ai can help to cut emissions and the use of pesticides , fertilisers , chemicals and water; further stresses that ai can contribute to the restoration of biodiversity and prevent deforestation by monitoring endangered species and tracking deforestation activities through smart forests; ### 33. believes that ai can have a transformative role in the agricultural sector when it comes to tackling food security issues , enabling the emergence of new harvesting methods and harvest prediction , novel approaches to food processing and retail , agricultural resource management and input efficiency , as well as improved land management and the optimisation of food supply chains; stresses that agriculture is a key sector in which ai can help to cut emissions and the use of pesticides , fertilisers , chemicals and water; further stresses that ai can contribute to the restoration of biodiversity and prevent deforestation by monitoring endangered species and tracking deforestation activities through smart forests; highlights the need for developing deployment guidelines and standardised assessment methodologies to support ‘green ai’ in areas such as smart grids , precision farming , and smart and sustainable cities as well as communities; is of the opinion that ai in the form of precision farming holds the potential to disrupt on-farm production of food as well as broader land management by improving land use planning , predicting land use change and monitoring crop health whilst having the potential to transform the prediction of extreme weather events;


### 33. believes that ai can have a transformative role in the agricultural sector when it comes to tackling food security issues , enabling the emergence of new harvesting methods and harvest prediction , novel approaches to food processing and retail , agricultural resource management and input efficiency , as well as improved land management and the optimisation of food supply chains; stresses that agriculture is a key sector in which ai can help to cut emissions and the use of pesticides , fertilisers , chemicals and water; further stresses that ai can contribute to the restoration of biodiversity and prevent deforestation by monitoring endangered species and tracking deforestation activities through smart forests; ### 33. believes that ai can have a transformative role in the agricultural sector , namely on food security , enabling the emergence of new harvesting methods and harvest prediction , agricultural resource management and input efficiency , as well as improved land management and the optimisation of food supply chains; stresses that agriculture is a key sector in which ai can help cut emissions and the use of pesticides , fertilisers , chemicals and water by optimizing their use to the exact amount and in a narrower area; further stresses that ai can contribute to the restoration of biodiversity by monitoring endangered species and tracking deforestation activities;


### 34. stresses that ai contributes to a circular economy through increased production output and quality , reduced maintenance costs , better use and the ethical sourcing of raw materials , and reduced waste; highlights that ai has the potential to automatically provide businesses with detailed insight into their emissions , including value chains , and forecast future emissions , thus helping to adjust and achieve individual emission targets; underlines that digital tools help businesses to implement the necessary steps towards more sustainable conduct , especially small and medium-sized enterprises (smes) which do not otherwise have the resources to do so; ### 34. stresses that ai can contribute to the circular economy through increased production output and quality , reduced maintenance costs , better use and the ethical sourcing of raw materials , and reduced waste; highlights that ai has the potential to automatically provide businesses with detailed insight into their emissions , including value chains , and forecast future emissions , thus helping adjust and achieve individual emission targets; underlines that digital tools help businesses implement the necessary steps towards more sustainable conduct , especially small and medium-sized enterprises (smes) which do not otherwise have the resources to do so;