Models & Labs · United States

DOE, NIH, and Biohub Partner to Build Foundational Data for Predictive Biological AI Models

Credited to HPCwire · hpcwire.com · 7h ago

WASHINGTON and SAN FRANCISCO, Oct. 9, 2026 — The Department of Energy’s (DOE) Office of Science, the National Institutes of Health (NIH), and Biohub signed a Memorandum of Understanding (MOU) to advance the frontier of Artificial Intelligence (AI) in biology, deepen our understanding of human health and disease, and accelerate breakthroughs in medicine and biotechnology.

The partnership brings together the computational powerhouse and biological expertise of DOE’s National Laboratories, Biohub’s AI technologies and biomedical research infrastructure, and NIH’s extensive health data, imaging resources, and research enterprise to build an open biological data foundation for predictive models of living systems and accurately predict how cells respond to various interventions.

“Advancing [Artificial] Intelligence in biology represents a critical step forward in leveraging new technologies for public benefit,” said DOE Under Secretary for Science Darío Gil. “By uniting the capabilities and expertise of DOE’s National Laboratories with philanthropic and scientific leadership, we are setting a new standard for open, data-driven science, accelerating discoveries, and solidifying American leadership in [AI]-driven biotechnology.”

DOE is investing more than $500 million over five years in fundamental cell research spanning data collection, AI analytics, laboratory measurement and imaging, modeling, and computation. Complementing this effort, Biohub is investing $500 million over five years in the Virtual Biology Initiative (VBI), a global effort to develop technologies and multi-modal datasets for predictive models of life.

“An accurate predictive model of biology could dramatically accelerate scientific discovery by enabling scientists to perform experiments digitally. The insights that come from this could unlock a far greater understanding of disease and open up completely new paths for cures,” said Biohub Head of Science, Alex Rives. “Because of this potential, the creation of a virtual cell is one of the most important challenges for the next era of science. It will require coordinated data generation efforts at a national and international scale, which is why these partners are coming together. We invite the worldwide scientific community to join us in this project.”

The partnership delivers for the Genesis Mission by leveraging AI-ready biological data, automated laboratory experiments, advanced modeling approaches, and state-of-the-art resources across DOE’s National Laboratory system, including:

Models & LabsUnited States

Sen. Cantwell Unveils Six-Point Plan to Govern Frontier AI

Credited to Broadband Breakfast · broadbandbreakfast.com8h ago

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WASHINGTON, Oct. 9, 2026 - A leading Senate Democrat is calling for strict artificial intelligence control to protect the public from preventable harms.

Sen. Maria Cantwell (D-Wash.), the top Democrat on the Senate Commerce Committee, has released a comprehensive governance framework for “frontier” artificial intelligence systems, calling for enforceable federal safety standards, continuous independent testing and strict accountability for developers.

The Oct. 7, 2026 proposal lays out six principles that Cantwell says must underpin any future AI legislation or executive action to address catastrophic risks, from AI-enabled cyberattacks to loss of human control over autonomous systems.

At the core of Cantwell’s plan is a major role for the National Institute of Standards and Technology, working with agencies such as Energy and Defense, to develop risk-based, measurable safety standards for AI systems that could cause catastrophic harm.

Those standards would explicitly address AI-enabled cyberattacks, chemical and biological threats, loss of human control including autonomous agents escaping secure test environments, and systems capable of self-improvement that could bypass safety controls. The framework also calls for specialized rules for open-source models, aiming to reduce misuse risks while giving developers clear guidance to maintain U.S. leadership in open AI ecosystems.

Cantwell argues that frontier models should not be released until they undergo independent, comprehensive audits similar to financial statement audits for public companies. Key elements include continuous oversight by government and qualified independent experts, stress-testing of models against catastrophic-risk scenarios, especially where testing requires secure facilities or sensitive information, and built-in safeguards so systems halt any self-modification that could evade monitoring or human oversight.

Developers would be required to give auditors the access and information needed to assess risks, investigate serious incidents and verify that safeguards work as intended.

Under the framework, AI developers would face new disclosure and reporting obligations modeled on securities-style risk disclosures, including plain-language public disclosures of material safety and security risks and how they are mitigated, prompt incident reporting for events such as loss of control over autonomous agents, dangerous cyber capabilities and critical safeguard failures, and whistleblower protections for employees and contractors who report safety, security or compliance concerns.

Cantwell also emphasizes that developers must remain liable under civil and criminal law for foreseeable harms where their design, deployment or failure to implement reasonable safeguards materially contributes to the damage.

Original · Broadband Breakfast

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Models & Labs · United States

We Need to Embed Ethics Into Our Engineering Courses

Credited to IEEE Spectrum · spectrum.ieee.org · 10h ago

Photograph · IEEE Spectrum

In mid-September, Anthropic CEO Dario Amodei joined a growing group of researchers calling for the AI industry to slow down. While some have questioned these researchers’ motivation for voicing concerns about the rapid pace of development, the plea highlighted a key tension between safety and speed. The underlying problem is not simply a technical error, but a sociotechnical failure: Pressure to move quickly has made it hard for engineers to fully assess and manage new risks of increasingly powerful AI systems. It is a clear warning that responsible engineering requires more than technical expertise; engineers must also understand workplace pressures, moral and ethical rules, and the social consequences rooted in the systems they create.

Cases like this, alongside invasive surveillance technologies and biased AI tools, have exposed serious shortcomings in how engineers recognize and address the ethical and social implications of their work. While the need to educate graduates in ethics and social responsibility is widely recognized, a persistent gap remains—these topics are too often treated as afterthoughts, disconnected from the technical content of engineering coursework. This siloed approach leaves graduates ill-equipped to address real-world challenges; indeed, only about a third of engineering professionals in the United States report having received training on their public welfare responsibilities during their formal engineering education.

We are working to bridge this gap by designing two complementary instructional approaches, one that integrates social issues directly into foundation technical coursework and a second that prepares students to act as “public welfare watchdogs” through a standalone engineering course. By embedding ethics and social responsibility training directly into the core of undergraduate engineering coursework, we equip future professionals with the agency they will need to protect the public good.

The gap in instruction about ethics and social responsibility

Across the engineering profession, there is a persistent belief that technical skill-building is central to engineering, while ethical, social, and public welfare concerns are peripheral or distracting. This technical/social dualism is evident even in the evaluation of scholarly research. For instance, we recently submitted an academic position paper discussing this ethics education gap to a leading peer-reviewed engineering journal. It was dismissed by reviewers along the very same dualism it described.

One reviewer warned that it would be “highly irresponsible” to challenge technical skill-building as “the foundation of any kind of engineering” by adding ethics and social responsibility training into engineering classrooms. Another reviewer objected that integrating these considerations into foundational courses risks “distracting the students from fully absorbing the technology.” These comments miss the core argument of our work: that ethics and social responsibility are integral to responsible technical practice.

Today, accreditation agencies like ABET (formerly known as the Accreditation Board for Engineering and Technology) and professional licensing bodies like the National Society of Professional Engineers mandate student outcomes related to social and public welfare consequences. But these curriculum requirements tend to be unhelpfully generic and minimally enforced. As a result, engineering students often receive ethics instruction through introductory or non-engineering coursework, where the focus is on codes of conduct and academic integrity, rather than deeper topics of social responsibility. This instruction is almost always disconnected from the complex real-world dilemmas engineers face.

Indeed, we find that only ethics instruction in actual engineering courses (not in other parts of the curriculum) can effectively instill ethical awareness as professionals. Concerningly, only about 4 in 10 engineers in the United States recall receiving this kind of training, and 3 in 10 report never receiving training on their public welfare responsibilities at any point in their careers. This leaves most of the profession underprepared to handle the complex challenges of engineering practice.

A new approach: Integrating technical and social dimensions

To advance a new paradigm—one that embeds ethics and social responsibility issues within the undergraduate engineering curriculum—we’ve designed two innovative course-based approaches: a library of one-hour sociotechnical modules for foundational circuits courses (described here and here ) and a new engineering course dedicated to public welfare responsibilities.

The first approach integrates discussions about relevant social issues directly into foundational engineering courses, where students begin to form their identities as engineers. “Introduction to Circuits” is typically the first course in the electrical engineering major and is a requirement for many other engineering disciplines, making it a powerful site for introducing social content and ethical reasoning. We designed several one-hour modules for this course, where social issues provide context for a technical topic, offering a manageable entry point for faculty who may feel ill-prepared to teach about ethics and social responsibility.

While many engineering faculty recognize the importance of teaching students about these topics, they struggle to integrate them into their courses amid heavy teaching and research demands. To overcome these challenges, each module provides ready-to-use materials, including lecture slides with scripts and homework and exam problems. Integrating these modules directly into the course signals to students that sociotechnical awareness is not an “add-on,” but a required professional competency.

Our module on hospital power prioritization, for instance, connects the technical topics of power and equivalent circuits to the ethical challenges of healthcare infrastructure. Students learn about the reality of “red outlets” in medical settings, debating the power needs of specific wards (e.g., the intensive care unit, operating rooms, and physiotherapy rooms) to decide which branches should receive emergency power during a hypothetical outage.

Our conflict minerals module connects the technical topic of capacitors to the global tantalum supply chain. Students calculate the amount of tantalum used in cell phones and identify mining locations in regions like the Democratic Republic of the Congo, where revenue often fuels armed conflict and human rights abuses. Students research the conflict-mineral policies of major companies such as Apple and Samsung and reflect on their future roles as ethical designers and consumers.

Student responses to these modules have been overwhelmingly positive. In interviews, students told us that the content helped them get away from the “stigma that engineers only worry about math” and made the work more meaningful. We plan to share the modules widely to help circuits instructors across the globe bridge the technical-social divide.

Beyond these integrated modules, our second approach is a standalone engineering course—Public Welfare Responsibilities in Engineering (PWRE)—that helps round out students’ sociotechnical education by preparing them to fulfil their professional obligations as engineers. While most dedicated ethics courses end by introducing engineers’ abstract responsibilities, PWRE helps students recognize specific public welfare concerns, enhances their motivation to act when they encounter them, and teaches concrete, practical intervention strategies.

In addition to teaching students about professional codes, such as the IEEE Code of Ethics, PWRE engages students in discussion of where these formal definitions may fall short, and how structural barriers such as workplace culture can hinder engineers from fulfilling these responsibilities. Then, the course equips students with intervention strategies. Students learn about their rights and responsibilities as whistleblowers, review tactics for seeking advice from professional societies, and practice writing op-eds to raise the alarm about ethical issues to the broader public. Our research shows that the course produces notable shifts in students’ ethical agency, strengthening their ability to serve as “public welfare watchdogs” in the modern workplace.

Ethical engineers for the future

Today’s engineering graduates face complex sociotechnical challenges beyond AI expansion, including climate change and global supply chains; they need tools to navigate ambiguity and act ethically in uncertain contexts. To meet these evolving demands, engineering education must move beyond outdated modes of instruction that focus only on building technical skills—some of which may soon be outsourced to AI. We must fundamentally reimagine the role of ethics and social responsibility, embedding them across the engineering curriculum and throughout the professional formation of engineers.

All engineers learn to solve problems, but ethical engineers can also discern which problems are worth solving and anticipate the consequences of innovation for society. By centering ethics and social responsibility as core priorities of the profession, we can prepare engineers to be stewards of technology and trusted voices in public discourse.

As one student reflected after participating in our modules, “we are a part of the issue if we don’t decide to fix it.”