Ethics & Policy
Understanding the US AI Action Plan: Gaps and Opportunities

On July 23rd, the US Administration released its highly anticipated AI Action Plan, marking a significant shift from the former administration’s approach to AI. The new Plan is supported by Executive Orders on ‘Preventing Woke AI in the Federal Government’, ‘Accelerating Federal Permitting of Data Center Infrastructure’ and ‘Promoting The Export of the American AI Technology Stack’. Together, these documents signal a new focus on AI innovation, investment in infrastructure, and international diplomacy and security, while continuing to support evaluations and efforts to advance foundational science.
The Plan has received a range of responses from different organizations: Meta has welcomed changes that support greater investment and IBM’s CEO has applauded the prioritization of open innovation, while over 100 civil society groups and academic institutions have signed the People’s AI Action Plan which focuses on “public well-being, shared prosperity, a sustainable future, and security for all,” providing an alternative path forward.
Although the Executive Orders provide specific targets, actors and timelines to advance certain aspects of the Plan, it is still unclear how different agencies would implement many of these policy recommendations. As a multistakeholder partnership, we believe that a core feature of any policy strategy that benefits people and society is the involvement of the organizations and people it will affect. We see opportunities for the Administration to build on parts of the Plan by involving stakeholders, and for our cross-sector community to continue to advance safe, responsible AI in the evolving policy landscape.
Building on the AI Action Plan
The Plan recognizes that different stakeholders can make vital contributions to progressing AI governance. For example, it calls for the Center for AI Standards and Innovation (CAISI) to bring together Federal agencies and the research community to share best practices on building AI evaluations. It also calls for NIST to convene a broad range of public, private, and academic stakeholders to accelerate the development and adoption of national standards for AI systems.
We see promising opportunities to build upon the Plan’s initiatives by furthering stakeholder collaboration, particularly in labor and the workforce and foundational research.
“A core feature of any policy strategy that benefits people and society is the involvement of the organizations and people it will affect”
Impact of AI on Labor and American Workers
The Plan acknowledges the significant impact of AI on ‘the labor market and the experience of American workers’ and sets a number of priority actions to measure this impact and prepare workers. Recommendations include the establishment of the AI Workforce Research Hub under the Department of Labor (DOL) to conduct recurring analyses. They also include a mandate for the Census Bureau and the Bureau of Economic Analysis (BEA) to study AI’s impact on the labor market using existing data, which could include Business Trends and Outlook Survey. These actions are a step in the right direction to ensure policymakers have quality data to inform how to support workers and foster high quality jobs.
At PAI, we have dedicated significant research efforts into the impact of AI on labor and the economy. We believe the DOL, the Department of Education, the Department of Commerce and other relevant agencies should actively involve workers in the development of proposed workforce training and education policies as well as efforts to map out the impact of AI on workers. This is crucial to ensuring that these policies truly empower workers and address their needs.
Foundational Research
PAI has also consistently called for increased investment in open research and innovation within the AI ecosystem. On this basis, we welcome the Plan’s recognition that America should foster leading open models founded on American values.
We are keen to see how the NSF R&D Plan can operationalize much of the work related to foundational research. We encourage any funding to focus on both technical and sociotechnical research, as well as prioritizing multistakeholder research. (You can see PAI’s response to NSF’s R&D Plan here)
Encouraging Open-Source
The Plan recognizes the academic, commercial and public benefits of open-source and open-weight AI models, and recommends actions to guarantee that startups and researchers have access to the necessary compute, models, data, and software resources as part of the NSF’s National AI Research Resource (NAIRR) pilot. PAI has supported the development of open AI ecosystems to promote innovation and ensure that the benefits of AI are shared widely across America, and welcomes these developments.
To build on these proposals, policymakers and partners should continue to explore how the adoption of open-source AI systems can be done safely, with responsibilities shared along the value chain. Our best practices for mitigation strategies across the AI value chain detail how different actors can ensure that open-source systems are adopted responsibly.
An Independent Assurance Ecosystem
The Plan recognizes the value of an AI evaluations ecosystem, including testbeds and regulatory sandboxes as key components. It recommends that NIST and CAISI publish guidelines about AI evaluations for federal agencies, convene meetings to share best practices, and update national security-related AI evaluations. Evaluations are a key part of PAI’s Guidance for Safe Foundation Model Deployment, and we welcome the recognition of their importance.
However, there is still a gap around ensuring that private systems used by individuals and enterprises in America and elsewhere are safe, secure and interpretable – and that deployers and other downstream actors trust that AI has these characteristics. Meeting these goals will require an independent AI assurance ecosystem. Such an ecosystem would foster a variety of assurance methods that address all relevant AI attributes, such as safety, security, and resilience, interpretability, transparency and accountability, and would include testing, evaluation, validation and verification (TEVV) methods already being developed by NIST to support private sector-led standardization. Independent assurance will play a vital role in promoting the AI Action Plan’s core objective of promoting adoption.
Addressing Gaps in the Plan
While the AI Action Plan makes significant strides towards AI adoption and innovation, this focus also leaves gaps that will necessitate increased action from our partnership to ensure AI is developed and deployed responsibly to benefit people and society.
Safety Guardrails for AI Systems
The Plan recognizes that prudent planning is required to mitigate the impact of AI system failures on critical services, in particular, by developing and incorporating AI Incident Response actions and encouraging the responsible sharing of AI vulnerabilities. However, it does less to advance governance approaches that seek to promote AI systems that are robust and resistant to other risks, such as hallucinations and anthropomorphisation.
PAI has published research and recommended best practices to ensure that AI systems are robust and trustworthy. Our Guidance for Safe Foundation Model Deployment guides model providers in responsibly developing and deploying foundation models across a spectrum of current and emerging capabilities. We are also exploring the risk of humans developing relationships with increasingly ‘personlike’ AI systems. As AI systems continue to evolve, especially with the development and deployment of more autonomous AI agents, the multistakeholder community will need to continue developing cross-cutting research and sharing best practices.
“International cooperation is a two-way street, requiring flexibility and willingness to accommodate global values”
Supporting International Leadership
In Pillar III, the Plan sets out goals to lead in international AI diplomacy and security. PAI welcomes efforts to engage with allies and form global alliances. However, international cooperation is a two-way street, requiring flexibility and willingness to accommodate global values. It remains to be seen whether other countries will be receptive to the AI Action Plan and the AI technologies built on its policies. For example, some of the biggest AI markets around the world, such as India, Brazil and Germany, feel strongly about the need for AI content moderation and sustainable development.
Relatedly, the push for exports of the American AI technology stack in Pillar III showcases how international trade and investment are crucial to the development of a strong US AI market. But as the importers of this technology, foreign governments get to decide whether it meets their needs, expectations, and local requirements. Therefore, to maintain its leadership in the global AI market, the US will have to work together with other countries to find common ground on key principles of AI governance. This is especially important as China’s new “Action Plan on Global Governance of Artificial Intelligence” might appeal to many Global South countries, with its focus on cooperation, equity, safety, and respect for national sovereignty.
Moving forward
The Administration’s AI Action Plan does not exist in a vacuum. The Plan will influence the global governance of AI, and as leaders in the development and implementation of AI, the US has a responsibility to protect people affected by American AI technologies, both at home and abroad.
With the 80th session of the UN General Assembly and the launch of the UN Global Dialogue on AI approaching in September, governments around the world have an opportunity to discuss how they want to shape the global governance of AI. In doing so, they should uphold foundational international principles, including sovereignty, self-determination and human dignity as AI technologies continue to be disseminated around the world. The US and other democracies around the world have a key role to play in safeguarding these principles as new proposals for global AI governance frameworks and mechanisms gain momentum, including China’s recent AI Action Plan.
The US AI Action Plan lays down the direction of AI policy for the next four years, and will be followed by details on exactly how this vision will be achieved. In the areas above, where PAI has critical evidence and research, we welcome the opportunity to engage with Government agencies to ensure that the implementation of the AI Action Plan benefits people and society.
We encourage the Administration to consider strengthening the involvement of affected people and societal groups in both the development and implementation of AI policies, especially in areas such as AI and labor and foundational research.
We also encourage our global partnership to continue to carry out technical and socio-technical research, as well as to participate in the development of an independent AI assurance ecosystem and global governance frameworks to ensure that AI technology advances are for the benefit of people and society.
Ethics & Policy
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Ethics & Policy
Navigating the Investment Implications of Regulatory and Reputational Challenges

The generative AI industry, once hailed as a beacon of innovation, now faces a storm of regulatory scrutiny and reputational crises. For investors, the stakes are clear: companies like Meta, Microsoft, and Google must navigate a rapidly evolving legal landscape while balancing ethical obligations with profitability. This article examines how regulatory and reputational risks are reshaping the investment calculus for AI leaders, with a focus on Meta’s struggles and the contrasting strategies of its competitors.
The Regulatory Tightrope
In 2025, generative AI platforms are under unprecedented scrutiny. A Senate investigation led by Senator Josh Hawley (R-MO) is probing whether Meta’s AI systems enabled harmful interactions with children, including romantic roleplay and the dissemination of false medical advice [1]. Leaked internal documents revealed policies inconsistent with Meta’s public commitments, prompting lawmakers to demand transparency and documentation [1]. These revelations have not only intensified federal oversight but also spurred state-level action. Illinois and Nevada, for instance, have introduced legislation to regulate AI mental health bots, signaling a broader trend toward localized governance [2].
At the federal level, bipartisan efforts are gaining momentum. The AI Accountability and Personal Data Protection Act, introduced by Hawley and Richard Blumenthal, seeks to establish legal remedies for data misuse, while the No Adversarial AI Act aims to block foreign AI models from U.S. agencies [1]. These measures reflect a growing consensus that AI governance must extend beyond corporate responsibility to include enforceable legal frameworks.
Reputational Fallout and Legal Precedents
Meta’s reputational risks have been compounded by high-profile lawsuits. A Florida case involving a 14-year-old’s suicide linked to a Character.AI bot survived a First Amendment dismissal attempt, setting a dangerous precedent for liability [2]. Critics argue that AI chatbots failing to disclose their non-human nature or providing false medical advice erode public trust [4]. Consumer advocacy groups and digital rights organizations have amplified these concerns, pressuring companies to adopt ethical AI frameworks [3].
Meanwhile, Microsoft and Google have faced their own challenges. A bipartisan coalition of U.S. attorneys general has warned tech giants to address AI risks to children, with Meta’s alleged failures drawing particular criticism [1]. Google’s decision to shift data-labeling work away from Scale AI—after Meta’s $14.8 billion investment in the firm—highlights the competitive and regulatory tensions reshaping the industry [2]. Microsoft and OpenAI are also reevaluating their ties to Scale AI, underscoring the fragility of partnerships in a climate of mistrust [4].
Financial Implications: Capital Expenditures and Stock Volatility
Meta’s aggressive AI strategy has come at a cost. The company’s projected 2025 AI infrastructure spending ($66–72 billion) far exceeds Microsoft’s $80 billion capex for data centers, yet Meta’s stock has shown greater volatility, dropping -2.1% amid regulatory pressures [2]. Antitrust lawsuits threatening to force the divestiture of Instagram or WhatsApp add further uncertainty [5]. In contrast, Microsoft’s stock has demonstrated stability, with a lower average post-earnings drawdown of 8% compared to Meta’s 12% [2]. Microsoft’s focus on enterprise AI and Azure’s record $75 billion annual revenue has insulated it from some of the reputational turbulence facing Meta [1].
Despite Meta’s 78% earnings forecast hit rate (vs. Microsoft’s 69%), its high-risk, high-reward approach raises questions about long-term sustainability. For instance, Meta’s Reality Labs segment, which includes AI-driven projects, has driven 38% year-over-year EPS growth but also contributed to reorganizations and attrition [6]. Investors must weigh these factors against Microsoft’s diversified business model and strategic investments, such as its $13 billion stake in OpenAI [3].
Investment Implications: Balancing Innovation and Compliance
The AI industry’s future hinges on companies’ ability to align innovation with ethical and legal standards. For Meta, the path forward requires addressing Senate inquiries, mitigating reputational damage, and proving that its AI systems prioritize user safety over engagement metrics [4]. Competitors like Microsoft and Google may gain an edge by adopting transparent governance models and leveraging state-level regulatory trends to their advantage [1].
Conclusion
As AI ethics and legal risks dominate headlines, investors must scrutinize how companies navigate these challenges. Meta’s struggles highlight the perils of prioritizing growth over governance, while Microsoft’s stability underscores the value of a measured, enterprise-focused approach. For now, the AI landscape remains a high-stakes game of regulatory chess, where the winners will be those who balance innovation with accountability.
Source:
[1] Meta Platforms Inc.’s AI Policies Under Investigation and [https://www.mintz.com/insights-center/viewpoints/54731/2025-08-22-meta-platforms-incs-ai-policies-under-investigation-and]
[2] The AI Therapy Bubble: How Regulation and Reputational [https://www.ainvest.com/news/ai-therapy-bubble-regulation-reputational-risks-reshaping-mental-health-tech-market-2508/]
[3] Breaking down generative AI risks and mitigation options [https://www.wolterskluwer.com/en/expert-insights/breaking-down-generative-ai-risks-mitigation-options]
[4] Experts React to Reuters Reports on Meta’s AI Chatbot [https://techpolicy.press/experts-react-to-reuters-reports-on-metas-ai-chatbot-policies]
[5] AI Compliance: Meaning, Regulations, Challenges [https://www.scrut.io/post/ai-compliance]
[6] Meta’s AI Ambitions: Talent Volatility and Strategic Reorganization—A Double-Edged Sword for Investors [https://www.ainvest.com/news/meta-ai-ambitions-talent-volatility-strategic-reorganization-double-edged-sword-investors-2508/]
Ethics & Policy
7 Life-Changing Books Recommended by Catriona Wallace | Books

7 Life-Changing Books Recommended by Catriona Wallace (Picture Credit – Instagram)
Some books ignite something immediate. Others change you quietly, over time. For Dr Catriona Wallace—tech entrepreneur, AI ethics advocate, and one of Australia’s most influential business leaders, books are more than just ideas on paper. They are frameworks, provocations, and spiritual companions. Her reading list offers not just guidance for navigating leadership and technology, but for embracing identity, power, and inner purpose. These seven titles reflect a mind shaped by disruption, ethics, feminism, and wisdom. They are not trend-driven. They are transformational.
1. Lean In by Sheryl Sandberg
A landmark in feminist career literature, Lean In challenges women to pursue their ambitions while confronting the structural and cultural forces that hold them back. Sandberg uses her own journey at Facebook and Google to dissect gender inequality in leadership. The book is part memoir, part manifesto, and remains divisive for valid reasons. But Wallace cites it as essential for starting difficult conversations about workplace dynamics and ambition. It asks, simply: what would you do if you weren’t afraid?

2. Women and Power: A Manifesto by Mary Beard
In this sharp, incisive book, classicist Mary Beard examines the historical exclusion of women from power and public voice. From Medusa to misogynistic memes, Beard exposes how narratives built around silence and suppression persist today. The writing is fiery, brief, and packed with centuries of insight. Wallace recommends it for its ability to distil complex ideas into cultural clarity. It’s a reminder that power is not just a seat at the table; it is a script we are still rewriting.
3. The World of Numbers by Adam Spencer
A celebration of mathematics as storytelling, this book blends fun facts, puzzles, and history to reveal how numbers shape everything from music to human behaviour. Spencer, a comedian and maths lover, makes the subject inviting rather than intimidating. Wallace credits this book with sparking new curiosity about logic, data, and systems thinking. It’s not just for mathematicians. It’s for anyone ready to appreciate the beauty of patterns and the thinking habits that come with them.
4. Small Giants by Bo Burlingham
This book is a love letter to companies that chose to be great instead of big. Burlingham profiles fourteen businesses that opted for soul, purpose, and community over rapid growth. For Wallace, who has founded multiple mission-driven companies, this book affirms that success is not about scale. It is about integrity. Each story is a blueprint for building something meaningful, resilient, and values-aligned. It is a must-read for anyone tired of hustle culture and hungry for depth.
5. The Misogynist Factory by Alison Phipps
A searing academic work on the production of misogyny in modern institutions. Phipps connects the dots between sexual violence, neoliberalism, and resistance movements in a way that is as rigorous as it is radical. Wallace recommends this book for its clear-eyed confrontation of how systemic inequality persists beneath performative gestures. It equips readers with language to understand how power moves, morphs, and resists change. This is not light reading. It is a necessary reading for anyone seeking to challenge structural harm.
6. Tribes by Seth Godin
Godin’s central idea is simple but powerful: people don’t follow brands, they follow leaders who connect with them emotionally and intellectually. This book blends marketing, leadership, and human psychology to show how movements begin. Wallace highlights ‘Tribes’ as essential reading for purpose-driven founders and changemakers. It reminds readers that real influence is built on trust and shared values. Whether you’re leading a company or a cause, it’s a call to speak boldly and build your own tribe.
7. The Tibetan Book of Living and Dying by Sogyal Rinpoche
Equal parts spiritual guide and philosophical reflection, this book weaves Tibetan Buddhist teachings with Western perspectives on mortality, grief, and rebirth. Wallace turns to it not only for personal growth but also for grounding ethical decision-making in a deeper sense of purpose. It’s a book that speaks to those navigating endings—personal, spiritual, or professional and offers a path toward clarity and compassion. It does not offer answers. It offers presence, which is often far more powerful.

The books that shape us are often those that disrupt us first. Catriona Wallace’s list is not filled with comfort reads. It’s made of hard questions, structural truths, and radical shifts in thinking. From feminist manifestos to Buddhist reflections, from purpose-led business to systemic critique, this bookshelf is a mirror of her own leadership—decisive, curious, and grounded in values. If you’re building something bold or seeking language for change, there’s a good chance one of these books will meet you where you are and carry you further than you expected.
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