This is a guest post. The views expressed here are solely those of the authors and do not represent positions of IEEE Spectrum, The Institute, or IEEE.

Many in the civilian artificial intelligence community don’t seem to realize that today’s AI innovations could have serious consequences for international peace and security. Yet AI practitioners—whether researchers, engineers, product developers, or industry managers—can play critical roles in mitigating risks through the decisions they make throughout the life cycle of AI technologies.

There are a host of ways by which civilian advances of AI could threaten peace and security. Some are direct, such as the use of AI-powered chatbots to create disinformation for political-influence operations. Large language models also can be used to create code for cyberattacks and to facilitate the development and production of biological weapons.

Other ways are more indirect. AI companies’ decisions about whether to make their software open-source and in which conditions, for example, have geopolitical implications. Such decisions determine how states or nonstate actors access critical technology, which they might use to develop military AI applications, potentially including autonomous weapons systems.

AI companies and researchers must become more aware of the challenges, and of their capacity to do something about them.

What Needs to Change in AI Education

Responsible AI requires a spectrum of capabilities that are typically not covered in AI education. AI should no longer be treated as a pure STEM discipline but rather a transdisciplinary one that requires technical knowledge, yes, but also insights from the social sciences and humanities. There should be mandatory courses on the societal impact of technology and responsible innovation, as well as specific training on AI ethics and governance.

Those subjects should be part of the core curriculum at both the undergraduate and graduate levels at all universities that offer AI degrees.

Changing the AI education curriculum is no small task. In some countries, modifications to university curricula require approval at the ministry level. Proposed changes can be met with internal resistance due to cultural, bureaucratic, or financial reasons. Meanwhile, the existing instructors’ expertise in the new topics might be limited.

An increasing number of universities now offer the topics as electives, however, including Harvard, New York University, Sorbonne University, Umeå University, and the University of Helsinki.

Adding Responsible AI to Lifelong Learning

The AI community must develop continuing education courses on the societal impact of AI research so that practitioners can keep learning about such topics throughout their career.

AI is bound to evolve in unexpected ways. Identifying and mitigating its risks will require ongoing discussions involving not only researchers and developers but also people who might directly or indirectly be impacted by its use. A well-rounded continuing education program would draw insights from all stakeholders.

Engaging With the Wider World

We also need AI practitioners to share knowledge and ignite discussions about potential risks beyond the bounds of the AI research community.

Fortunately, there are already numerous groups on social media that actively debate AI risks including the misuse of civilian technology by state and nonstate actors. There are also niche organizations focused on responsible AI that look at the geopolitical and security implications of AI research and innovation. They include the AI Now Institute, the Centre for the Governance of AI, Data and Society, the Distributed AI Research Institute, the Montreal AI Ethics Institute, and the Partnership on AI.

Those communities, however, are currently too small and not sufficiently diverse, as their most prominent members typically share similar backgrounds. Their lack of diversity could lead the groups to ignore risks that affect underrepresented populations.

We must find ways to grow the existing communities, make them more diverse and inclusive, and make them better at engaging with the rest of society. Large professional organizations such as IEEE and ACM could help, perhaps by creating dedicated working groups of experts or setting up tracks at AI conferences.

Universities and the private sector also can help by creating or expanding positions and departments focused on AI’s societal impact and AI governance. Umeå University recently created an AI Policy Lab to address the issues. Companies including Anthropic, Google, Meta, and OpenAI have established divisions or units dedicated to such topics.

The central question before regulators is whether AI researchers and companies can be trusted to develop the technology responsibly.

In our view, one of the most effective and sustainable ways to ensure that AI developers take responsibility for the risks is to invest in education. Practitioners of today and tomorrow must have the basic knowledge and means to address the risk stemming from their work if they are to be effective designers and implementers of future AI regulations.