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Ford CEO Jim Farley warns AI will wipe out half of white-collar jobs

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Ford CEO Jim Farley recently became the latest corporate boss to sound the alarm about artificial intelligence’s impact on workers.

During the Aspen Ideas Festival last week, he highlighted the importance of the “essential economy”—which he defined as everything that gets moved, built or fixed—while saying blue-collar skilled trades have been neglected.

The U.S. spends too little on vocational training, which is also geared more toward 1950 than 2050, contributing to a decline in blue-collar productivity, Farley explained, though the carmaker has been investing in training.

Meanwhile, demand for skilled trades is expected to surge, and even the AI boom will require workers to build and service the facilities that provide all the computing capacity that’s needed.

There’s already a massive shortage of trade workers, he added, estimating a deficit of 600,000 in factories and nearly half a million in construction, for example.

“There’s more than one way to the American dream, but our whole education system is focused on four-year [college] education,” Farley said. “Hiring an entry worker at a tech company has fallen 50% since 2019. Is that really where we want all of our kids to go? Artificial intelligence is gonna replace literally half of all white-collar workers in the U.S.” 

His AI warning marked that latest from a top CEO about AI’s impact on the labor force, especially on office workers.

Last month, Amazon CEO Andy Jassy said the company’s corporate workforce will shrink in the next few years due to AI.

“We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs,” Jassy wrote in a memo to employee. “It’s hard to know exactly where this nets out over time, but in the next few years, we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.”

In addition, Anthropic CEO Dario Amodei told Axios in May that AI could eliminate half of all entry-level white-collar jobs, sending the unemployment rate as high as 20% in the next five years. The latest employment report showed the jobless rate was at 4.1% in June.

There are already signs that AI is threatening the types of jobs that historically have served as stepping stones for young workers.

LinkedIn’s chief economic opportunity officer, Aneesh Raman, pointed out in May that AI tools are doing the types of simple coding and debugging tasks that junior software developers did to gain experience. AI is also doing work that young employees in the legal and retail sectors once did.

For his part, Ford’s CEO sought to draw attention to the opportunity in skilled trades, noting that more Americans are also considering trade school than a four-year college.

“We all sense that America can do better than we are doing,” Farley said last week. “We need a new mindset, one that recognizes the success the importance of this essential economy and the importance to our vibrancy and sustainability as a country.”



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Scientists create biological ‘artificial intelligence’ system

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Australian scientists have successfully developed a research system that uses ‘biological artificial intelligence’ to design and evolve molecules with new or improved functions directly in mammal cells. The researchers said this system provides a powerful new tool that will help scientists develop more specific and effective research tools or gene therapies. Named PROTEUS (PROTein Evolution Using Selection) the system harnesses ‘directed evolution’, a lab technique that mimics the natural power of evolution. However, rather than taking years or decades, this method accelerates cycles of evolution and natural selection, allowing them to create molecules with new functions in weeks. This could have a direct impact on finding new, more effective medicines. For example, this system can be applied to improve gene editing technology like CRISPR to improve its effectiveness.

Journal/conference: Nature Communications

Research: Paper

Organisation/s: The University of Sydney



Funder: Declaration: Alexandar Cole, Christopher Denes, Daniel Hesselson and Greg Neely have filed a provisional patent application on this technology The remaining authors declare no competing interests.

Media release

From: The University of Sydney

Australian scientists have successfully developed a research system that uses ‘biological artificial intelligence’ to design and evolve molecules with new or improved functions directly in mammal cells. The researchers said this system provides a powerful new tool that will help scientists develop more specific and effective research tools or gene therapies.

Named PROTEUS (PROTein Evolution Using Selection) the system harnesses ‘directed evolution’, a lab technique that mimics the natural power of evolution. However, rather than taking years or decades, this method accelerates cycles of evolution and natural selection, allowing them to create molecules with new functions in weeks.

This could have a direct impact on finding new, more effective medicines. For example, this system can be applied to improve gene editing technology like CRISPR to improve its effectiveness.

“This means PROTEUS can be used to generate new molecules that are highly tuned to function in our bodies, and we can use it to make new medicine that would be otherwise difficult or impossible to make with current technologies.” says co-senior author Professor Greg Neely, Head of the Dr. John and Anne Chong Lab for Functional Genomics at the University of Sydney.

“What is new about our work is that directed evolution primarily work in bacterial cells, whereas PROTEUS can evolve molecules in mammal cells.”

PROTEUS can be given a problem with uncertain solution like when a user feeds in prompts for an artificial intelligence platform. For example the problem can be how to efficiently turn off a human disease gene inside our body.

PROTEUS then uses directed evolution to explore millions of possible sequences that have yet to exist naturally and finds molecules with properties that are highly adapted to solve the problem. This means PROTEUS can help find a solution that would normally take a human researcher years to solve if at all.

The researchers reported they used PROTEUS to develop improved versions of proteins that can be more easily regulated by drugs, and nanobodies (mini versions of antibodies) that can detect DNA damage, an important process that drives cancer. However, they said PROTEUS isn’t limited to this and can be used to enhance the function of most proteins and molecules.

The findings were reported in Nature Communications, with the research performed at the Charles Perkins Centre, the University of Sydney with collaborators from the Centenary Institute.

Unlocking molecular machine learning

The original development of directed evolution, performed first in bacteria, was recognised by the 2018 Noble Prize in Chemistry.

“The invention of directed evolution changed the trajectory of biochemistry. Now, with PROTEUS, we can program a mammalian cell with a genetic problem we aren’t sure how to solve. Letting our system run continuously means we can check in regularly to understand just how the system is solving our genetic challenge,” said lead researcher Dr Christopher Denes from the Charles Perkins Centre and School of Life and Environmental Sciences

The biggest challenge Dr Denes and the team faced was how to make sure the mammalian cell could withstand the multiple cycles of evolution and mutations and remain stable, without the system “cheating” and coming up with a trivial solution that doesn’t answer the intended question.

They found the key was using chimeric virus-like particles, a design consisting of taking the outside shell of one virus and combining it with the genes of another virus, which blocked the system from cheating.

The design used parts of two significantly different virus families creating the best of both worlds. The resulting system allowed the cells to process many different possible solutions in parallel, with improved solutions winning and becoming more dominant while incorrect solutions instead disappear.

“PROTEUS is stable, robust and has been validated by independent labs. We welcome other labs to adopt this technique. By applying PROTEUS, we hope to empower the development of a new generation of enzymes, molecular tools and therapeutics,” Dr Denes said.

“We made this system open source for the research community, and we are excited to see what people use it for, our goals will be to enhance gene-editing technologies, or to fine tune mRNA medicines for more potent and specific effects,” Professor Neely said.

-ENDS-



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AI can provide ’emotional clarity and confidence’ Xbox executive producer tells staff after Microsoft lays off 9,000 employees

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  • An Xbox executive suggested that laid-off employees use AI for emotional support and career guidance
  • The suggestion sparked backlash and led the executive to delete their LinkedIn post
  • Microsoft has laid off 9,000 employees in recent months while investing heavily in AI.

Microsoft has been hyping up its AI ambitions for the last several years, but one executive’s pitch about the power of AI to former employees who were recently let go has landed with an awkward thud.

Amid the largest round of layoffs in over two years, about 9,000 people, Matt Turnbull, Executive Producer at Xbox Game Studios Publishing, suggested that AI chatbots could help those affected process their grief, craft resumes, and rebuild their confidence.



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Regulatory Policy and Practice on AI’s Frontier

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Adaptive, expert-led regulation can unlock the promise of artificial intelligence.

Technological breakthroughs, historically, have played a distinctive role in accelerating economic growth, expanding opportunity, and enhancing standards of living. Technology enables us to get more out of the knowledge we have and prior scientific discoveries, in addition to generating new insights that enable new inventions. Technology is associated with new jobs, higher incomes, greater wealth, better health, educational improvements, time-saving devices, and many other concrete gains that improve people’s day-to-day lives. The benefits of technology, however, are not evenly distributed, even when an economy is more productive and growing overall. When technology is disruptive, costs and dislocations are shouldered by some more than others, and periods of transition can be difficult.

Theory and experience teach that innovative technology does not automatically improve people’s station and situation merely by virtue of its development. The way technology is deployed and the degree to which gains are shared—in other words, turning technology’s promise into reality without overlooking valid concerns—depends, in meaningful part, on the policy, regulatory, and ethical decisions we make as a society.

Today, these decisions are front and center for artificial intelligence (AI).

AI’s capabilities are remarkable, with profound implications spanning health care, agriculture, financial services, manufacturing, education, energy, and beyond. The latest research is demonstrably pushing AI’s frontier, advancing AI-based reasoning and AI’s performance of complex multistep tasks, and bringing us closer to artificial general intelligence (high-level intelligence and reasoning that allows AI systems to autonomously perform highly complex tasks at or beyond human capacity in many diverse instances and settings). Advanced AI systems, such as AI agents (AI systems that autonomously complete tasks toward identified objectives), are leading to fundamentally new opportunities and ways of doing things, which can unsettle the status quo, possibly leading to major transformations.

In our view, AI should be embraced while preparing for the change it brings. This includes recognizing that the pace and magnitude of AI breakthroughs are faster and more impactful than anticipated. A terrific indication of AI’s promise is the 2024 Nobel Prize in chemistry, winners of which used AI to “crack the code” of protein structures, “life’s ingenious chemical tools.” At the same time, as AI becomes widely used, guardrails, governance, and oversight should manage risks, safeguard values, and look out for those disadvantaged by disruption.

Government can help fuel the beneficial development and deployment of AI in the United States by shaping a regulatory environment conducive to AI that fosters the adoption of goods, services, practices, processes, and tools leveraging AI, in addition to encouraging AI research.

It starts with a pro-innovation policy agenda. Once the goal of promoting AI is set, the game plan to achieve it must be architected and implemented. Operationalizing policy into concrete progress can be difficult and more challenging when new technology raises novel questions infused with subtleties.

Regulatory agencies that determine specific regulatory requirements and enforce compliance play a significant part in adapting and administering regulatory regimes that encourage rather than stifle technology. Pragmatic regulation compatible with AI is instrumental so that regulation is workable as applied to AI-led innovation, further unlocking AI’s potential. Regulators should be willing to allow businesses flexibility to deploy AI-centered uses that challenge traditional approaches and conventions. That said, regulators’ critical mission of detecting and preventing harmful behavior should not be cast aside. Properly calibrated governance, guardrails, and oversight that prudently handle misuse and misconduct can support technological advancement and adoption over time.

Regulators can achieve core regulatory objectives, including, among other things, consumer protection, investor protection, and health and safety, without being anchored to specific regulatory requirements if the requirements—fashioned when agentic and other advanced AI was not contemplated—are inapt in the context of current and emerging AI.

We are not implying that vital governmental interests that are foundational to many regulatory regimes should be jettisoned. Rather, it is about how those interests are best achieved as technology changes, perhaps dramatically. It is about regulating in a way that allows AI to reach its promise and ensuring that essential safeguards are in place to protect persons from wrongdoing, abuses, and harms that could frustrate AI’s real-world potential by undercutting trust in—and acceptance of—AI. It is about fostering a regulatory environment that allows for constructive AI-human collaboration—including using AI agents to help monitor other AI agents while humans remain actively involved addressing nuances, responding to an AI agent’s unanticipated performance, engaging matters of greatest agentic AI uncertainty, and resolving tough calls that people can uniquely evaluate given all that human judgment embodies.

This takes modernizing regulation—in its design, its detail, its application, and its clarity—to work, very practically, in the context of AI by accommodating AI’s capabilities.

Accomplishing this type of regulatory modernity is not easy. It benefits from combining technological expertise with regulatory expertise. When integrated, these dual perspectives assist regulatory agencies in determining how best to update regulatory frameworks and specific regulatory requirements to accommodate expected and unexpected uses of advanced AI. Even when underpinning regulatory goals do not change, certain decades-old—or newer—regulations may not fit with today’s technology, let alone future technological breakthroughs. In addition, regulatory updates may be justified in light of regulators’ own use of AI to improve regulatory processes and practices, such as using AI agents to streamline permitting, licensing, registration, and other types of approvals.

Regulatory agencies are filled with people who bring to bear valuable experience, knowledge, and skill concerning agency-specific regulatory domains, such as financial services, antitrust, food, pharmaceuticals, agriculture, land use, energy, the environment, and consumer products. That should not change.

But the commissions, boards, departments, and other agencies that regulate so much of the economy and day-to-day life—the administrative state—should have more technological expertise in-house relevant to AI. AI’s capabilities are materially increasing at a rapid clip, so staying on top of what AI can do and how it does it—including understanding leading AI system architecture and imagining how AI might be deployed as it advances toward its frontier—is difficult. Without question, there are individuals across government with impressive technological chops, and regulators have made commendable strides keeping apprised of technological innovation. Indeed, certain parts of government are inherently technology-focused. Many regulatory agencies are not, however; but even at those agencies, in-depth understanding of AI is increasingly important.

Regulatory agencies should bring on board more individuals with technology backgrounds from the private sector, academia, research institutions, think tanks, and elsewhere—including computer scientists, physicists, software engineers, AI researchers, cryptographers, and the like.

For example, we envision a regulatory agency’s lawyers working closely with its AI engineers to ensure that regulatory requirements contemplate and factor in AI. Lawyers with specific regulatory knowledge can prompt large language models to measure a model’s interpretation of legal and regulatory obligations. Doing this systematically and with a large enough sample size requires close collaboration with AI engineers to automate the analysis and benchmark a model’s results. AI engineers could partner with an agency’s regulatory experts in discerning the technological capabilities of frontier AI systems to comport with identified regulatory objectives in order to craft regulatory requirements that account for and accommodate the use of AI in consequential contexts. AI could accelerate various regulatory functions that typically have taken considerable time for regulators to perform because they have demanded significant human involvement. To illustrate, regulators could use AI agents to assist the review of permitting, licensing, and registration applications that individuals and businesses must obtain before engaging in certain activities, closing certain transactions, or marketing and selling certain products. Regulatory agencies could augment humans by using AI systems to conduct an initial assessment of applications and other requests against regulatory requirements.

The more regulatory agencies have the knowledge and experience of technologists in-house, the more understanding regulatory agencies will gain of cutting-edge AI. When that enriched technological insight is combined with the breadth of subject-matter expertise agencies already possess, regulatory agencies will be well-positioned to modernize regulation that fosters innovation while preserving fundamental safeguards. Sophisticated technological know-how can help guide regulators’ decisions concerning how best to revise specific regulatory features so that they are workable with AI and conducive to technological progress. The technical elements of regulation should be informed by the technical elements of AI to ensure practicable alignment between regulation and AI, allowing AI innovation to flourish without incurring undue risks.

With more in-house technological expertise, we think regulatory agencies will grow increasingly comfortable making the regulatory changes needed to accommodate, if not accelerate, the development and adoption of advanced AI.

There is more to technological progress that propels economic growth than technological capability in and of itself. An administrative state that is responsive to the capabilities of AI—including those on AI’s expanding frontier—could make a big difference converting AI’s promise into reality, continuing the history of technological breakthroughs that have improved people’s lives for centuries.

Troy A. Paredes



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