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On May 21, 2021, the U.S. Consumer Products Safety Commission (“CPSC”) published a report on artificial intelligence (AI) and machine learning (ML) in consumer products. The report highlights recent CPSC staff activity concerning AI and ML, proposes a framework for evaluating the potential safety impact of AI and ML capabilities in consumer products, and makes several recommendations that the CPSC can take in identifying and addressing potential hazards related to AI and ML capabilities in consumer products.

Concerning staff activity, CPSC recently hired a Chief Technologist with a background in AI and ML to address the use of AI in consumer products. The CPSC also recently established an “AI/ML Working Group” and held a virtual forum on AI and ML in March 2021.

Informed by the discussions held with various stakeholders at this forum, the CPSC staff has proposed a framework in the report for evaluating the potential safety impact of AI and ML in consumer products. The framework’s first step involves screening products for AI and ML “components.” The CPSC and stakeholders have identified the following components to be essential to producing an AI capability: data sources, algorithms, computations, and connections. Likewise, the CPSC and stakeholders have found the following components to define ML capabilities: assessing and monitoring outputs, analyzing and modeling changes, and adjusting and adapting behavior over time. The framework’s second step involves assessing the functions and features of consumer products’ AI and ML capabilities. The third step involves understanding how products’ AI and ML capabilities may impact consumers, which can be accomplished by studying the nature of the technology, how it is implemented in the product, and how the consumer might use the product. The final step involves ascertaining if, and to what extent, AI and ML capabilities may transform the product and/or its use over time.
Continue Reading CPSC Publishes Report on Artificial Intelligence and Machine Learning

This article was originally published in Automotive World.

The future of the mobility is dependent on AI, but without greater understanding among consumers, trust could be hard to build.

The mobility sector is keen to realise the full benefits of artificial intelligence (AI), not least to open up the revenues which data-driven connected services could offer. But moving forward, it must balance these opportunities with the rights of drivers, passengers and pedestrians. A number of concerns have already surfaced, all of which will become more pressing as the technology is further embedded into vehicles, mobility services and infrastructure.

Privacy and liability are two of the major challenges. As Christian Theissen, Partner, White & Case explains, mobility has become inherently connected to consumer habits and behavioural patterns, much like the e-commerce and social media industries. “The access, ownership, storage and transmission of personal data, such as driving patterns, must be taken into consideration by both lawmakers and companies gathering and using data,” he says. Meanwhile, in a world of AI-powered self-driving, at what point do regulators start blaming the machine when something goes wrong?

Part of the challenge in considering these issues is that as things stand, there is limited understanding among consumers around what rights there are. “Consumers appreciate AI,” says Cheri Falvey, Partner, Crowell & Moring, “and in particular the ease with which navigational apps help guide them to their destination. Whether they appreciate how their data is accumulating and developing a record of their mobility patterns, and what their rights are in respect to that data, is another question.”

There is often little precedent for regulators to rely on when making new policy in this arena, so it’s a good time to create a proactive regulatory strategy that invites discussion and collaboration from the start

This is in part because it is not always clear when AI is at work. A driver may register when a car’s navigation system learns the way home, but won’t necessarily realise that data on how a car is driven is being collected for predictive maintenance purposes, or that their data is being fed into infrastructure networks to manage traffic flow.


Continue Reading Automakers and Regulators Must Educate Consumers on Mobility AI