On May 23rd, the United States Department of Education published a report offering insights and recommendations on the application of artificial intelligence (AI) in education.
Biden admin emphasizes the necessity of ‘equity’ in AI
This comes as part of a series of announcements by President Biden’s administration stressing the need for “equity” in AI.
The report posits that potential biases found in AI algorithms should be acknowledged and addressed to prevent perpetuating or introducing unjust, discriminatory practices in education.
However, it leaves ambiguous the department’s stance on whether they consider certain discriminatory practices as just—for instance, affirmative action, a subject of an imminent Supreme Court verdict.
Report sheds light on possible benefits of AI
The authors of the report shed light on some perceived beneficial prospects that AI brings. Among them are strategies to compensate for the learning setbacks brought about by the pandemic and the enhancement of adaptability and personalization in digital learning tools.
These tools are seen as particularly advantageous for students with disabilities, multilingual students, and more.
Despite recognizing these potential benefits, the authors express their reservations about certain personalization forms when discussing “algorithmic discrimination”—loosely defined as unfairness in learning opportunities or resources suggested to specific student groups.
They express concern that if AI algorithms adjust curriculum pace based on incomplete data or biased learning assumptions, this could exacerbate educational achievement disparities.
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Student surveillance, teacher job security discussed
However, concerns about equity and group discrepancies aren’t the sole issues raised in the report. It also addresses student surveillance, teacher job security, and other areas.
The authors categorically dismiss the notion that AI could supplant teachers, terming it a risk of utmost importance.
According to the authors, the analysis partly sprang from four listening sessions conducted in 2022 that included over 700 participants.
‘Racial equity’ and ‘unfair bias’ central themes in discussions
Racial equity and unfair bias emerged as central themes in every session. The feedback from “educational constituents” led them to conclude that AI tools and systems should reflect a shared vision of high-quality learning, which includes equity.
The report underscores the necessity for educational systems to manage their AI use due to the potential for bias. Despite outlining these suggestions, the authors make it clear that the recommendations are not legally binding.
The Department of Education’s report was released following a sequence of AI-related announcements by the Biden administration stressing “racial equity.”
An official disclosed that President Biden believes Congress should legislate against algorithmic discrimination in the private sector.
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VP Harris held discussions with Microsoft, OpenAI, Alphabet
Subsequently, Vice President Kamala Harris held discussions with top executives at Microsoft, OpenAI, Alphabet, and Anthropic on the responsible use of AI in their offerings.
On the same day, Microsoft unveiled a new AI content moderation service named “Azure Content Safety.” According to Microsoft, the service can identify harmful content and assign severity scores, allowing businesses to prioritize content for review.
Further AI-related announcements from the administration on May 23rd involved amendments to the National AI R&D Strategic Plan, first initiated under President Obama in 2016 and later updated under President Donald Trump in 2019.
Equity is a central theme of the plan.
The administration also initiated a Request for Information (RFI) for its National AI Strategy, with the inquiries within the RFI reflecting the administration’s interest in equity in AI.
The questions in the RFI focus on ensuring AI promotes equal opportunity, mitigates algorithmic discrimination, and advances positive outcomes for all, as well as how existing laws and policies could be revised to account for inequitable impacts from AI systems.
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