Uploaded November 2022 | Updated September 2026, 2 weeks ago
Modern drones have been around for a few decades. They provide strategic surveillance and air-strike capabilities while removing human pilots from harm. Early drones were essentially controlled remotely by pilots at a safe distance from the battlefield, but modern military drones are increasingly operated autonomously by artificial intelligence (AI) computer systems. Where does the human fit into the decision-making process?
In this video, James Rogers, DIAS Associate Professor in War Studies at the University of Southern Denmark, non-resident senior fellow at Cornell University and associate fellow at the London School of Economics, explores the three types of human involvement: in the loop, on the loop and outside the loop. Right now, humans are in the loop by piloting and operating the weapons remotely. On the loop means that the human isn’t in direct control at all times but takes control over any decisions the machine makes. Lastly, and of most concern, is when the human is outside the loop of control. In the near future, AI-powered drones could execute entire missions without human intervention, only reporting back the result after the attack is complete.
Rogers argues that a human should always be in the loop of control when the fate of another human being is at risk — these decisions should never be left in the hands of a computer.
Read the essay here: cigionline.org/articles/the-third-drone-age-visions-out-to-2040
Modern drones have been around for a few decades. They provide strategic surveillance and air-strike capabilities while removing human pilots from harm. Early drones were essentially controlled remotely by pilots at a safe distance from the battlefield, but modern military drones are increasingly operated autonomously by artificial intelligence (AI) computer systems. Where does the human fit into the decision-making process?
In this video, James Rogers, DIAS Associate Professor in War Studies at the University of Southern Denmark, non-resident senior fellow at Cornell University and associate fellow at the London School of Economics, explores the three types of human involvement: in the loop, on the loop and outside the loop. Right now, humans are in the loop by piloting and operating the weapons remotely. On the loop means that the human isn’t in direct control at all times but takes control over any decisions the machine makes. Lastly, and of most concern, is when the human is outside the loop of control. In the near future, AI-powered drones could execute entire missions without human intervention, only reporting back the result after the attack is complete.
Rogers argues that a human should always be in the loop of control when the fate of another human being is at risk — these decisions should never be left in the hands of a computer.
Read the essay here: cigionline.org/articles/the-third-drone-age-visions-out-to-2040
![Big Tech - S3E09 - Mutale Nkonde on How Biased Tech Design and Racial Disparity Intersect
In this episode of Big Tech, Taylor Owen speaks with Mutale Nkonde, founder of AI for the People (AFP). She shares her experiences of discrimination and bias working in journalism and at tech companies in Silicon Valley. Moving into government, academia and activism, Nkonde has been able to bring light to the ways in which biases baked into technology’s design disproportionately affect racialized communities. For instance, during the 2020 US presidential campaign, her communications team was able to detect and counter groups who were targeting Black voters in social media groups, by weaponizing misinformation, with the specific message to not vote. In her role with AFP, she works to produce content that empowers people to combat racial bias in tech. One example is the “ban the scan” advocacy campaign with Amnesty International, which seeks to ban the use of facial recognition technology by government agencies.
In their conversation, Mutale and Taylor discuss the many ways in which technology reflects and amplifies bias. Many of the issues begin when software tools are designed by development teams that lack diversity or actively practise forms of institutional racism, excluding or discouraging decision-making participation by minority ethnic group members. Another problem is the data sets included in training the systems; as Nkonde explains, “Here in the United States, if you’re a white person, 70 percent of white people don’t actually know a Black person. So, if I were to ask one of those people to bring me a hundred pictures from their social media, it’s going to be a bunch of white people.” When algorithms that are built with this biased data make it into products — for use in, say, law enforcement, health care and financial services — they begin to have serious impacts on people’s lives, most severely when law enforcement misidentifies a suspect. Among the cases coming to light, “in New Jersey, Nijeer Parks was not only misidentified by a facial recognition system, arrested, but could prove that he was 30 miles away at the time,” Nkonde recounts. “But, because of poverty, [Parks] ended up spending 10 days in jail, because he couldn’t make bail. And that story really shows how facial recognition kind of reinforces other elements of racialized violence by kind of doubling up these systems.” Which is why Nkonde is working to ban facial recognition technology from use, as well as fighting for other legislation in the United States that will go beyond protecting individual rights to improving core systems for the good of all.
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