Artificial intelligence

Experts urge broader values in AI development

Since the launch of ChatGPT in late 2023, the private sector has led AI innovation. Major players like Microsoft, Google, and Alibaba—alongside emerging firms such as Anthropic and Mistral—are racing to monetise AI and secure long-term growth in the technology-driven economy.

But during the Fortune Brainstorm AI conference in Singapore this week, experts stressed the importance of human values in shaping AI’s future. Anthea Roberts, founder of Dragonfly Thinking, argued that AI must be built not just to think faster or cheaper, but also to think better.

She highlighted the risk of narrow thinking—national, disciplinary or algorithmic—and called for diverse, collaborative thinking to counter it. Roberts sees potential in human-AI collaboration, which can help policymakers explore different perspectives, boosting the chances of sound outcomes.

Russell Wald, executive director at Stanford’s Institute for Human-Centred AI, called AI a civilisation-shifting force. He stressed the need for an interdisciplinary ecosystem—combining academia, civil society, government and industry—to steer AI development.

‘Industry must lead, but so must academia,’ Wald noted, as well as universities’ contributions to early research, training, and transparency. Despite widespread adoption, AI scepticism persists, due to issues like bias, hallucination, and unpredictable or inappropriate language.

Roberts said most people fall into two camps: those who use AI uncritically, such as students and tech firms, and those who reject it entirely.

She labelled the latter as practising ‘critical non-use’ due to concerns over bias, authenticity and ethical shortcomings in current models. Inviting a broader demographic into AI governance, Roberts urged more people—especially those outside tech hubs like Silicon Valley—to shape its future.

Wald noted that in designing AI, developers must reflect the best of humanity: ‘Not the crazy uncle at the Thanksgiving table.’

Both experts believe the stakes are high, and the societal benefits of getting AI right are too great to ignore or mishandle. ‘You need to think not just about what people want,’ Roberts said, ‘but what they want to want—their more altruistic instincts.’

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Trump pushes for ‘anti-woke’ AI in US government contracts

Tech firms aiming to sell AI systems to the US government will now need to prove their chatbots are free of ideological bias, following a new executive order signed by Donald Trump.

The measure, part of a broader plan to counter China’s influence in AI development, marks the first official attempt by the US to shape the political behaviour of AI in services.

It places a new emphasis on ensuring AI reflects so-called ‘American values’ and avoids content tied to diversity, equity and inclusion (DEI) frameworks in publicly funded models.

The order, titled ‘Preventing Woke AI in the Federal Government’, does not outright ban AI that promotes DEI ideas, but requires companies to disclose if partisan perspectives are embedded.

Major providers like Google, Microsoft and Meta have yet to comment. Meanwhile, firms face pressure to comply or risk losing valuable public sector contracts and funding.

Critics argue the move forces tech companies into a political culture war and could undermine years of work addressing AI bias, harming fair and inclusive model design.

Civil rights groups warn the directive may sideline tools meant to support vulnerable groups, favouring models that ignore systemic issues like discrimination and inequality.

Policy analysts have compared the approach to China’s use of state power to shape AI behaviour, though Trump’s order stops short of requiring pre-approval or censorship.

Supporters, including influential Trump-aligned venture capitalists, say the order restores transparency. Marc Andreessen and David Sacks were reportedly involved in shaping the language.

The move follows backlash to an AI image tool released by Google, which depicted racially diverse figures when asked to generate the US Founding Fathers, triggering debate.

Developers claimed the outcome resulted from attempts to counter bias in training data, though critics labelled it ideological overreach embedded by design teams.

Under the directive, companies must disclose model guidelines and explain how neutrality is preserved during training. Intentional encoding of ideology is discouraged.

Former FTC technologist Neil Chilson described the order as light-touch. It does not ban political outputs; it only calls for transparency about generating outputs.

OpenAI said its objectivity measures align with the order, while Microsoft declined to comment. xAI praised Trump’s AI policy but did not mention specifics.

The firm, founded by Elon Musk, recently won a $200M defence contract shortly after its Grok chatbot drew criticism for generating antisemitic and pro-Hitler messages.

Trump’s broader AI orders seek to strengthen American leadership and reduce regulatory burdens to keep pace with China in the development of emerging technologies.

Some experts caution that ideological mandates could set a precedent for future governments to impose their political views on critical AI infrastructure.

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Big companies grapple with AI’s legal, security, and reputational threats

A recent Quartz investigation reveals that concerns over AI are increasingly overshadowing corporate enthusiasm, especially among Fortune 500 companies.

More than 69% now reference generative AI in their annual reports as a risk factor, while only about 30% highlight its benefits, a dramatic shift toward caution in corporate discourse.

These risks range from cybersecurity threats, such as AI-generated phishing, model poisoning, and adversarial attacks, to operational and reputational dangers stemming from opaque AI decision-making, including hallucinations and biassed outputs.

Privacy exposure, legal liability, task misalignment, and overpromising AI capabilities, so-called ‘AI washing’, compound corporate exposure, particularly for boards and senior leadership facing directors’ and officers’ liability risks.

Other structural risks include vendor lock-in, disproportionate market influence by dominant AI providers, and supply chain dependencies that constrain flexibility and resilience.

Notably, even cybersecurity experts warn of emerging threats from AI agents, autonomous systems capable of executing actions that complicate legal accountability and oversight.

Companies are advised to adopt comprehensive AI risk-management strategies to navigate this evolving landscape.

Essential elements include establishing formal governance frameworks, conducting bias and privacy audits, documenting risk assessments, ensuring human-in-the-loop oversight, revising vendor contracts, and embedding AI ethics into policy and training, particularly at the board level.

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Democratising inheritance: AI tool handles estate administration

Lauren Kolodny, who early backed Chime and earned a spot on the Forbes Midas list, is leading a $20 million Series A funding round into Alix, a San Francisco-based startup using AI to revolutionise estate settlement. Founder Alexandra Mysoor conceived the idea after spending nearly 1,000 hours over 18 months managing a friend’s family estate, highlighting a widespread, emotionally taxing administrative gap.

Using AI agents, Alix automates tedious elements of the estate process, including scanning documents, extracting data, pre-populating legal forms, and liaising with financial institutions. This contrasts sharply with the traditional, costly probate system. The startup’s pricing model charges around 1% of estate value, translating to approximately $9,000–$12,000 for smaller estates.

Kolodny sees Alix as part of a new wave of startups harnessing AI to democratise services once accessible only to high-net-worth individuals. As trillions of dollars transfer to millennials and Gen Z in the coming decades, Alix aims to simplify one of the most complex and emotionally fraught administrative tasks.

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Teachers and students warn: AI is eroding engagement

A student from San Jose and an English teacher in Chicago co-authored a Boston Globe opinion warning that widespread use of AI in schools damages the vital student-teacher bond.

While marketed as efficiency boosters, AI tools encourage students to forgo independent thinking.

Many simply generate entire assignments via AI, reformat the text to avoid detection, and undermine honest academic interaction.

Educators report feeling increasingly marginalised as AI handles much of their workload, including grading, lesson planning, and feedback within classrooms.

Though schools and tech companies promote these tools as educational enhancements, many schools have eroded trust, as teachers struggle to assess real student ability.

The authors call for a return to supervised in-class assignments, using pen and paper, strict scrutiny of AI vendors in education, and outright bans on unsupervised AI classroom tools to help reset the learning relationship.

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DeepSeek and others gain traction in US and EU

A recent survey has found that most US and the EU users are open to using Chinese large language models, even amid ongoing political and cybersecurity scrutiny.

According to the report, 71 percent of respondents in the US and 87 percent in the EU would consider adopting models developed in China.

The findings highlight increasing international curiosity about the capabilities of Chinese AI firms such as DeepSeek, which have recently attracted global attention.

While the technology is gaining credibility, many Western users remain cautious about data privacy and infrastructure control.

More than half of those surveyed said they would only use Chinese AI models if hosted outside China. However, this suggests that while trust in the models’ performance is growing, concerns over data governance remain a significant barrier to adoption.

The results come amid heightened global competition in the AI race, with Chinese developers rapidly advancing to challenge US-based leaders. DeepSeek and similar firms now face balancing global outreach with geopolitical limitations.

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Google’s AI Overviews reach 2 billion users monthly, reshaping the web’s future

Google’s AI Overviews, the generative summaries placed above traditional search results, now serve over 2 billion users monthly, a sharp rise from 1.5 billion just last quarter.

First launched in May 2023 and widely available in the US by mid-2024, the feature has rapidly expanded across more than 200 countries and 40 languages.

The widespread use of AI Overviews transforms how people search and who benefits. Google reports that the feature boosts engagement by over 10% for queries where it appears.

However, a study by Pew Research shows clicks on search results drop significantly when AI Overviews are shown, with just 8% of users clicking any link, and only 1% clicking within the overview itself.

While Google claims AI Overviews monetise at the same rate as regular search, publishers are left out unless users click through, which they rarely do.

Google has started testing ads within the summaries and is reportedly negotiating licensing deals with select publishers, hinting at a possible revenue-sharing shift. Meanwhile, regulators in the US and EU are scrutinising whether the feature violates antitrust laws or misuses content.

Industry experts warn of a looming ‘Google Zero’ future — a web where search traffic dries up and AI-generated answers dominate.

As visibility in search becomes more about entity recognition than page ranking, publishers and marketers must rethink how they maintain relevance in an increasingly post-click environment.

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Amazon exit highlights deepening AI divide between US and China

Amazon’s quiet wind-down of its Shanghai AI lab underscores a broader shift in global research dynamics, as escalating tensions between the US and China reshape how tech giants operate across borders.

Instead of expanding innovation hubs in China, major American firms are increasingly dismantling them.

The AWS lab, once central to Amazon’s AI research, produced tools said to have generated nearly $1bn in revenue and over 100 academic papers.

Yet its dissolution reflects a growing push from Washington to curb China’s access to cutting-edge technology, including restrictions on advanced chips and cloud services.

As IBM and Microsoft have also scaled back operations or relocated talent away from mainland China, a pattern is emerging: strategic retreat. Rather than risking compliance issues or regulatory scrutiny, US tech companies are choosing to restructure globally and reduce local presence in China altogether.

With Amazon already having exited its Chinese ebook and ecommerce markets, the shuttering of its AI lab signals more than a single closure — it reflects a retreat from joint innovation and a widening technological divide that may shape the future of AI competition.

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YouTube Shorts brings image-to-video AI tool

Google has rolled out new AI features for YouTube Shorts, including an image-to-video tool powered by its Veo 2 model. The update lets users convert still images into six-second animated clips, such as turning a static group photo into a dynamic scene.

Creators can also experiment with immersive AI effects that stylise selfies or simple drawings into themed short videos. These features aim to enhance creative expression and are currently available in the US, Canada, Australia and New Zealand, with global rollout expected later this year.

A new AI Playground hub has also been launched to house all generative tools, including video effects and inspiration prompts. Users can find the hub by tapping the Shorts camera’s ‘create’ button and then the sparkle icon in the top corner.

Google plans to introduce even more advanced tools with the upcoming Veo 3 model, which will support synchronised audio generation. The company is positioning YouTube Shorts as a key platform for AI-driven creativity in the video content space.

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US lawmaker proposes to train young Americans in AI for cyberwarfare

In a Washington Post opinion piece, Rep. Elise Stefanik and Stephen Prince, CEO of TFG Asset Management, argue that the United States is already engaged in a new form of warfare — cyberwarfare — waged by adversaries like China, Russia, and Iran using tools such as malware, phishing, and zero-day exploits. They assert that the US is not adequately prepared to defend against these threats due to a significant shortage of cyber talent, especially within the military and government.

To address this gap, the authors propose the creation of the United States Advanced Technology Academy (USATA) — a tuition-free, government-supported institution that would train a new generation of Americans in cybersecurity, AI, and quantum computing. Modelled after military academies, USATA would be located in upstate New York and require a five-year public service commitment from graduates.

The goal is to rapidly develop a pipeline of skilled cyber defenders, close the Pentagon’s estimated 30,000-person cyber personnel shortfall, and maintain US leadership in strategic technologies. Stefanik and Prince argue that while investing in AI tools and infrastructure is essential, equally critical is the cultivation of human expertise to operate, secure, and ethically deploy these tools. They position USATA not just as an educational institution but as a national security imperative.

The article places the academy within a broader effort to outpace rivals like China, which is also actively investing in STEM education and tech capacity. The authors call on the President to establish USATA via executive order or bipartisan congressional support, framing it as a decisive and forward-looking response to 21st-century threats.

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