Administration under President Biden Should Forgo Cautionary Measures for AI within Upcoming Regulatory Assessment, Opines Center for Data Innovation
In a recent statement, the Center for Data Innovation has emphasised the importance of maintaining a balanced approach to AI regulation, aiming to avoid harming innovation while ensuring safety and accountability. The organisation's proposed principles for AI regulation are designed to foster innovation, promote transparency, and protect consumers.
The statement expresses concern that current AI regulations could deviate from the U.S.'s historically innovation-friendly approach to the digital economy. The misguided notion that AI is inherently problematic could cloud the discussion on AI regulation. To address this, the Center for Data Innovation has proposed ten principles for AI regulation that aim to avoid harming innovation.
The principles focus on promoting innovation and economic growth, risk-based regulation, encouraging transparency and accountability, avoiding a patchwork of conflicting regulations, supporting research and entrepreneurship, recognising the diversity of AI technologies, protecting privacy and civil liberties, fostering collaboration between public and private sectors, ensuring human oversight and control, and providing regulatory clarity with timely updates.
The Center for Data Innovation advocates for a federal, harmonized, risk-based, and innovation-friendly regulatory framework. This approach stresses that effective AI regulation must carefully balance safety and accountability with the need to preserve the agility and innovation that drive AI progress, avoiding redundant or overly restrictive rules that could hamper the U.S. AI ecosystem.
In response to the statement, Hodan Omaar, senior policy analyst at the Center for Data Innovation, issued a statement. Omaar emphasised that the best way to protect consumers from potential harms of AI is not through new regulations, but by holding companies accountable for monitoring their use of algorithms.
To achieve this outcome, the administration can rigorously enforce existing laws and regulations and conduct a gap analysis to identify any shortcomings. The U.S. Commerce Department's National Telecommunications and Information Administration (NTIA) has recently requested comments on accountability measures for AI systems.
However, many proposals to regulate AI are based on the false premise that AI is fundamentally dangerous and consumers need government protection. This could lead to clouded discussions on AI regulation, potentially resulting in the United States becoming an AI follower, similar to Europe, posing a risk to U.S. innovation and competitiveness. The Center for Data Innovation's proposed principles aim to avoid this outcome, ensuring a balanced approach to AI regulation that encourages innovation while maintaining safety and accountability.
The Center for Data Innovation's proposed principles for AI regulation prioritize fostering innovation and economic growth, while also encouraging transparency and accountability. To achieve consumer protection, one suggests holding companies accountable for the use of algorithms through rigorous enforcement of existing laws and regulations. Advocating for a federal, harmonized, risk-based, and innovation-friendly regulatory framework, the Center aims to balance safety and accountability with the need to preserve agility and innovation in AI. In response to the statement, the Center for Data Innovation highlights that a balanced approach to AI regulation is crucial to maintain U.S. innovation and competitiveness, avoiding the pitfall of adopting regulations that consider AI as inherently dangerous, potentially leading to the U.S. becoming an AI follower like Europe.
