1050 K Street, NW | Suite 650 | Washington, DC 20001 | AutosInnovate.org

September 10, 2021

SUBMITTED VIA EMAIL

James A. St. Pierre

Acting Director 

Information Technology Laboratory

National Institute of Standards and Technology

100 Bureau Drive

Gaithersburg, MD 20899

Re: Request for Comments on A Proposal for Identifying and Managing Bias in Artificial 

Intelligence

Dear Acting Director St. Pierre: 

The Alliance for Automotive Innovation (“Auto Innovators”) appreciates this opportunity to 

provide input to the National Institute of Standards and Technology (“NIST”) in response to its Request 

for Comments on its recent A Proposal for Identifying and Managing Bias in Artificial Intelligence (“Draft 

Special Publication”). 

Auto Innovators is the singular, authoritative and respected voice of the automotive industry. 

Focused on creating a cleaner, safer, and smarter transportation future, Auto Innovators represents the 

manufacturers producing nearly 99 percent of cars and light trucks sold in the United States. Members of 

Auto Innovators include motor vehicle manufacturers, original equipment suppliers, technology 

companies and others within the automotive ecosystem. 

Our member companies are leaders in innovation and are integrating cutting-edge technologies 

into consumer vehicles that are redefining the future of mobility. A number of these innovations –

including automated driving and other advanced safety technologies, as well as other features that support 

drivers and passengers – incorporate or leverage artificial intelligence. For this reason, Auto Innovators 

shares NIST’s interest in and commitment to increasing public trust in artificial intelligence systems. 

We recognize that, while there are artificial intelligence use cases where there is very little 

possibility of harmful societal impacts from bias, there are certainly instances where biases that are present 

in artificial intelligence systems can lead to such impacts. We appreciate that reducing these harmful biases 

can help improve trust in these specific artificial intelligence systems and in artificial intelligence more 

broadly.
In general, we believe that the structure and themes identified in NIST’s proposal are appropriate

and flexible enough to accommodate application in a variety of contexts and use cases. We agree with 

NIST that, for more effective management and mitigation, it makes sense to associate applicable biases 

within specific stages modeled on the artificial intelligence lifecycle. That being said, we offer the 

following suggestions and comments to NIST with respect to its efforts:

• Emphasize High-Risk Applications Over Other Applications: The Draft Special Publication

acknowledges that artificial intelligence will be used in a variety of different contexts. Conceding 

that it is “difficult to develop overarching guidance or mitigation techniques,” NIST notes that its 

proposal “focuses on biases present in artificial intelligence systems that can lead to harmful 

societal outcomes.” However, the Draft Special Publication does not take any steps to distinguish 

or differentiate between biases that can lead to harmful societal outcomes and those that are 

unlikely to lead to such outcomes. Instead, the Draft Special Publication appears to propose a 

structure that would be universally applied in all contexts and across all industries without regard 

to the likelihood of harmful societal outcomes. Auto Innovators believes that high-risk applications 

should be emphasized in both this proposal and in upcoming work. Furthermore, to help promote 

trustworthiness and innovation, we encourage NIST to consider the development of best practices 

for assessing the risks posed by artificial intelligence systems to guide prioritization of risk 

mitigation efforts. 

• Recognize the Iterative and Cyclical Nature of Innovation: NIST proposes a three-stage 

approach derived from the artificial intelligence lifecycle with the intent of enabling artificial 

intelligence designers and deployers to better relate specific lifecycle processes with the types of 

artificial intelligence bias and facilitate more effective management of it. However, in the 

subsections detailing the proposed stages, there seems to be at least some potential overlap between 

the pre-design stage and the design and development stage and between the design and 

development stage and the deployment stage. For example, the selection of representative datasets 

is mentioned in the pre-design stage as well as in in the design and development stage. In addition, 

the suggestion to limit algorithmic decision-making tools for specific, well-defined use cases and 

not beyond those use cases is covered in both the design and development stage and the

deployment stage. 

Evidence of risks stemming from biases in artificial intelligence systems may present in later 

stages of the development lifecycle. In these cases, practitioners may iterate their products by 

revisiting earlier stages of development. To help ensure that this is a useful tool that can be used 

effectively by developers, we suggest that NIST recognize the iterative and cyclical nature of the 

process. Additionally, we urge NIST to acknowledge that these three stages are not clearly 

distinguishable linear stages, but instead are overlapping stages in an iterative cycle. We also urge 

NIST to consider developing guidance, including potential techniques, that developers can use to 

successfully apply this approach to their work. 

• Continue to Affirm Important Baseline Values: The Draft Special Publication includes 

important clarifications that should be maintained by NIST and adopted by other policymakers. 

Specifically, in the Draft Special Publication, NIST recognizes that “bias is neither new nor unique 
to artificial intelligence.” This essential point should continue to guide efforts by NIST and other 

policymakers related to bias in artificial intelligence. It is important to acknowledge that human 

decision-making may reflect inherent or implicit biases and, in some cases, artificial algorithmic 

decision-making may reduce, minimize, or even eliminate such biases. 

The Draft Special Publication further recognizes that the goal of NIST’s efforts is not “zero risk,” 

but rather to “identify, understand, measure, manage, and reduce bias.” Auto Innovators shares 

NIST’s belief that technology exhibiting zero risk is unlikely to be developed. If policymakers 

hold artificial intelligence developers to an unreasonable zero risk standard, important and – in 

some cases – lifesaving artificial intelligence-enabled applications may be lost. 

• Ensure Broad Stakeholder Engagement: The Draft Special Publication indicates a clear intent 

by NIST to obtain feedback from the broader community of interest and to host public events with 

a wide-ranging set of stakeholders. Auto Innovators shares NIST’s perspective that “the broader 

[artificial intelligence] community, practitioners, and users all have many valuable insights and 

recommendations to offer in managing and mitigating bias.” We firmly agree that efforts to 

identify which techniques to include in a framework that seeks to promote trustworthiness and 

responsibility in artificial intelligence, which has many use cases across many industries and 

contexts, requires an approach that is actively representative and includes a broad set of disciplines 

and stakeholders. 

• Incorporate Data Generation Provenance: NIST should consider incorporating data provenance 

into its work. For example, to minimize bias and realize beneficial uses of artificial intelligence, 

the provenance of the data – including where the data comes from and how it is collected - should 

be known, understood, and maintained as part of the modeling solution. Since instances of bias in 

artificial intelligence development can sometimes be addressed by filling gaps in the data that is 

used, understanding the origins of the data may help a developer more easily address bias that 

emerges during development or deployment. 

We appreciate your focus and attention on this important issue. We look forward to working with 

you to advance the deployment of trustworthy and responsible artificial intelligence in the United States 

and to help enable a cleaner, safer, and smarter transportation future. 

Sincerely,

Hilary M. Cain

Vice President

Technology, Innovation, & Mobility Policy