Data Innovation

Instead of focusing on imposing AI-specific guardrails, Australia’s regulatory framework should prioritize mechanisms for accountability, transparency, and traceability in decision-making processes, particularly within the public sector.

Governor Gavin Newsom’s veto of California’s AI safety bill (SB 1047) was a sensible move, but a deeper issue remains unresolved. A fundamental flaw of the bill lies in its approach to AI safety: it attempts to identify risky systems based solely on assessments made before deployment.

The EU should adopt a more flexible, innovation-driven approach to AI regulation to boost global competitiveness, according to the European Competitiveness Report by Mario Draghi.

As the United States commands the field with English-language large language models (LLMs) and China climbs the ranks to secure the lead in models for Chinese-language tasks, Europe is barely in the game when it comes to mastering models for its own languages.

The rise of generative AI tools, such as ChatGPT, has transformed text creation but also raises concerns about misuse, including plagiarism and misinformation. While some propose watermarking to label AI-generated content, this approach is technically flawed and ineffective, failing to address the root causes of these issues; instead, more comprehensive strategies are needed to combat misinformation and promote academic integrity.

The AIA came into law on 12th July 2024, triggering several actions by the AIO to ensure streamlined compliance with the new rules. The Center for Data Innovation puts forward six key recommendations to support AI innovation and adoption within the new framework.

AI presents a wealth of opportunity for the UK, not only as an economy boosting mechanism, but also as a tool for improving the lives of UK citizens. AI adoption is key to the Action Plan, and the government should take actions that can simultaneously support AI sector growth and AI adoption.

The UK's AI Opportunities Action Plan focuses on sector growth and adoption. The government should encourage lightweight models, invest in industry-academia partnerships, and establish sector centres to support AI uptake across industries.

The Center for Data Innovation submitted comments to the U.S. Artificial Intelligence Safety Institute (AISI) on its draft guidelines, Managing Misuse Risk for Dual-Use Foundation Models (NIST AI 800-1).

The Center for Data Innovation submitted comments to the Federal Communications Commission (FCC) regarding the disclosure and transparency of AI-generated content in political advertisements.