Euroviews. Future wars will be waged with robots. But so might future peace ǀ View

Future wars will be waged with robots. But so might future peace  ǀ View
By Daanish Masood, Martin Waehlisch
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The opinions expressed in this article are those of the author and do not represent in any way the editorial position of Euronews.

Artificial intelligence (AI) usually makes headlines for all the wrong reasons. [...] At the United Nations we have been exploring completely different scenarios for AI: its potential to be used for the noble purposes of peace and security.


Artificial intelligence (AI) usually makes headlines for all the wrong reasons: AI is being used to empower mass surveillance; AI will create autonomous weapons to make war-fighting more efficient; AI will revolutionise manufacturing – and take our jobs; AI will digitalise everything into the cloud – making us more vulnerable to hacking. At worst, AI might lead to the emergence of non-human consciousness which, Terminator-style, looks at humans as inferior – and seeks to wipe them out with its superior robotic technology.

Though touted as a real possibility by the likes of Elon Musk, that particular idea has been dismissed in the field as far-fetched. In his 2018 book, Ten Arguments for Deleting Your Social Media Accounts Now, polymathic computer scientist and ‘founding father’ of virtual reality Jaron Lanier described AI as a decades-old lie that he and others in Silicon Valley invented just to get money from DARPA, the US Pentagon agency responsible for researching technological breakthroughs.

Lanier was being tongue-in-cheek. His point was that despite our dystopian fears, AI is still far too rudimentary to pose an existential threat to the human species.

At the United Nations we have been exploring completely different scenarios for AI: its potential to be used for the noble purposes of peace and security. This could revolutionize the way of how we prevent and solve conflicts globally.

Two of the most promising areas are Machine Learning and Natural Language Processing. Machine Learning involves computer algorithms detecting patterns from data to learn how to make predictions and recommendations. Natural Language Processing involves computers learning to understand human languages.

At the UN Secretariat, our chief concern is with how these emerging technologies can be deployed for the good of humanity to de-escalate violence and increase international stability.

This endeavor has admirable precedent. During the Cold War, computer scientists used multilayered simulations to predict the scale and potential outcome of the arms race between the East and the West.

Since then, governments and international agencies have increasingly used computational models and advanced Machine Learning to try to understand recurrent conflict patterns, and forecast moments of state fragility.

But two things have transformed the scope for progress in this field.

The first is the sheer volume of data now available from what people say and do online. The second is the game-changing growth in computational capacity that allows us to crunch unprecedented, inconceivable quantities data with relative speed and ease.

So how can this help the United Nations build peace? Three ways come to mind.

Firstly, overcoming cultural and language barriers. By teaching computers to understand human language and the nuances of dialects, not only can we better link up what people write on social media to local contexts of conflict, we can also more methodically follow what people say on radio and TV. This can help us detect hate speech in a place where the potential for conflict is high as part of the UN’s early warning efforts.

This is crucial because the UN often works in countries where internet coverage is low, and where the spoken languages may not be well understood by many of its international staff.

Natural Language Processing algorithms can help to track and improve understanding of local debates – which might well be blind spots for the international community.

If we combine such methods with Machine Learning chatbots, the UN could conduct largescale digital focus groups with thousands in real-time, enabling different demographic segments in a country to voice their views on, say, a proposed peace deal – instantly testing public support, and indicating the chances of sustainability.

Secondly, anticipating the deeper drivers of conflict. We could combine new imaging techniques – whether satellites or drones – with automation. For instance, many parts of the world are experiencing severe groundwater withdrawal and water aquifer depletion.

Water scarcity in turn drives conflicts and undermines stability in post-conflict environments, where violence around water access becomes more likely, along with large movements of people leaving newly arid areas.

One of the best predictors of water depletion is land subsidence or sinking, which can be measured by satellite and drone imagery.


By combining these imaging techniques with Machine Learning, the UN can work in partnership with governments and local communities to anticipate future water conflicts and begin working proactively to reduce their likelihood.

Thirdly, advancing decision making. In the work of peace and security, it is surprising how many consequential decisions are still made solely on the basis of intuition.

Yet complex decisions often need to navigate conflicting goals and undiscovered options, against a landscape of limited information and political preference. This is where we can use Deep Learning – where a network can absorb huge amounts of public data and test it against real world examples on which it is trained; while applying with probabilistic modeling. This mathematical approach can help us to generate models of our uncertain, dynamic world with limited data.

With better data, we can eventually make better predictions to guide complex decisions. Future senior peace envoys charged with mediating a conflict would benefit from such advances to stress test elements of a peace agreement. Of course, human decision-making will remain crucial, but would be informed by more evidence-driven, robust analytical tools.

Doing the above inside the UN, which is equally enthusiastic and cautious about change, is no easy task. It will require training staff and senior leaders in new approaches and trusting in their competence.


And it will also require collaborating with university researchers, and forging close partnerships with leading private AI and technology firms.

The good news is that the work has already started. But we are still at baby-steps. With the Secretary-General’s support, including through his landmark Strategy on New Technologies, the time to scale this activity has come.

We can leave no stone unturned and no tool ignored to reduce violence and promote peace – that, after all, is the moral obligation at the very core of the UN Charter.

Daanish Masood and Martin Waehlisch are Political Affairs Officers at the UN's Department of Political and Peacebuilding Affairs

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