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.

The framework demonstrates the CPSC’s focus on the impact AI may have on the long-term safety of products that may operate differently as they evolve over time.  Identifying a defect that could present a safety risk can be challenging in an AI product because the product in the hands of consumers is not the same product that came off the manufacturing line.  If those changes over time could result in emerging safety issues, those risks would need to be reported to the CPSC.  The timing of those reports could be tricky if a defect emerges due to product transformations in only certain applications or use cases, but may not emerge in some or all products, or in all products at the same time given different usage patterns.  The framework appears to be designed to explore these issues.  It is also broad enough to allow the CPSC to do more than spot emerging defects and hazards.  It should also allow them to identify safety advantages in AI and ML technologies that may enable products to identify and mitigate potential hazards before they manifest thereby eliminating risks and increasing the overall safety of products.

The report also outlines a set of recommendations for future steps the CPSC can take to address AI and ML-related product safety concerns. First, the CPSC should continue building upon the discussions it held with stakeholders at the March 2021 forum. Second, and arguably most significantly, the CPSC should focus on voluntary standards development with respect to AI and ML, as it has done with other technologies. And it should leverage private-public partnerships to do so.

The CPSC also plans to address product testing. Product testing is important because, in the past, the CPSC has faced the challenge of replicating product safety incidents due to the constant changes in AI and ML technologies. The CPSC is also exploring different collaborative efforts with various stakeholders, including interagency agreements. Additionally, the CPSC has expressed a desire to work with investigators, data scientists, and AI and ML subject matter experts, to develop tools for them so that they too can work with the CPSC’s partner stakeholders, and to hire new staff with AI, ML, or related technical backgrounds. Given these plans and efforts, the CPSC is likely to prioritize AI and ML in its fiscal year 2022 Operating Plan.

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Analytics Insight recently published its first AI Review report to offer insights on how artificial intelligence service providers are positioned in the industry. Featuring four different categories, viz., Leaders, Disruptor, Pioneers, Challenger, the report highlights the top vendors in each category and points out their market scope and ability to disrupt the AI market.

The report has evaluated 15 artificial intelligence companies, taking into account their market influence and market potential, thus providing a 360-degree view of these vendors. The core factors in determining market influence include, area of focus, solutions, industries, market revenue and geographic presence. Whereas, the market potential is gauged using attributes like funding, innovation, and strategy. 

It is important to note that the vendor selection and assessment are based on key insights and attributes which were validated by analysts and inputs from global CXO advisors of Analytics Insight. Further, Analytics Insight does not endorse any vendor, product or service depicted in its AI Matrix report. 

Besides, this report aims to act as a reference for companies around the world when considering and selecting artificial intelligence service providers for various industrial functions. It can also help companies who want to analyze and compare their market competitors. This information can prove resourceful when attempting to improve one’s own company in areas where others are weak, giving them a market advantage.

Analytics Insight added in its report that, “Since the AI Matrix is a graphical presentation of a vendor’s strengths and capabilities, understanding this can enable business leaders to look for recommendations in the Artificial Intelligence niche, with respect to their business and technology needs.”

The contextualization by Analytics Insight is its attempt to give a quick snapshot of the notable players in the artificial intelligence industry. However, it advises companies not to select vendors only considering their ratings or other designation.

The Analytics Insight AI Matrix report has placed the top visionaries like Databricks, SenseTime, H2O.ai and DataRobot in the Leaders, while Dataiku, DeepMind, C3.ai and SentinelOne were positioned in the Pioneers’. On the other hand, the Disruptors  include Feedzai, Dataminr, AiBrain and Scale AI. Finally, vendors Nauto, Element AI and People.ai feature in Challengers. 

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