Scientist Urges Swift Policies to Address Real AI Risks

As AI reshapes society, policymakers must prioritize global tech regulation, IP reform, and readiness for workforce disruption.

These are the key points made by AI expert Professor Shalom Lappin, supported by thorough research in his new book, Understanding the Artificial Intelligence Revolution.

Lappin, who holds academic positions at Queen Mary University of London, King’s College London, and the University of Gothenburg, emphasizes that the public must play a central role in shaping the future development of AI technologies.

Rather than entertaining speculative fears about superintelligent machines, which he sees as disconnected from current engineering realities, Lappin focuses on pressing, real-world issues that demand urgent policy action.

Corporate Dominance Skews AI Research Toward Profit Over Public Interest

Lappin highlights the monopolization of AI by major tech firms as a major issue. In 2022, corporations developed 32 leading machine learning models, while universities produced only three. This imbalance, he argues, lets companies steer research toward profit-driven goals rather than the public good.

He also stresses the environmental toll of AI. For example, training ChatGPT-4 reportedly used around 50 gigawatt hours of electricity—comparable to the annual energy consumption of thousands of U.S. homes. Additionally, producing AI microchips requires toxic chemicals, substantial water resources, and immense power, with some chip factories using up to 100 megawatts per hour.

To tackle these pressing issues, Professor Lappin proposes several key policy actions. First, he calls for robust international regulation of tech giants, noting that individual nations often lack the capacity to enforce rules on a global scale. International trade agreements, he suggests, could serve as a vehicle for enforcing meaningful oversight.

Reforming Intellectual Property to Protect Creators in the Age of AI

Second, he advocates for reforming intellectual property laws to ensure that creators are fairly compensated when their work is used to train AI models. At the very least, companies should obtain consent from copyright holders and disclose the datasets used to train their systems, Lappin argues.

He also raises concerns about systemic bias in AI applications across sectors like healthcare, recruitment, and finance. To counter this, and to address issues like disinformation and hate speech online, Lappin emphasizes the need for policy-driven solutions—arguing that current self-regulation by tech firms falls short of protecting public interests.

The Rising Threat of Disinformation and Deepfakes in the AI Era

Lappin warns that disinformation and deepfakes pose a serious and growing threat. As generative AI advances, it becomes increasingly difficult to tell truth from fabrication.

“We may soon find ourselves in a world where distinguishing fact from harmful fiction is nearly impossible,” he cautions. “When that happens, the shared understanding that holds the public sphere together could collapse into mistrust and disorder.”

He also stresses the need for governments to address the risk of large-scale job displacement as AI-driven automation spreads across industries. Preventing widespread social disruption, he argues, will require major public investment in social services and new employment opportunities.

“These challenges cannot be left to the whims of the market or the dominant tech firms shaping it,” Lappin asserts.

Understanding the Artificial Intelligence Revolution also serves as a clear, accessible introduction to AI’s historical development and a concise explanation of today’s AI technologies.

Read the original article on: Techxplore

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