Artificial intelligence (AI) applications have attracted considerable ethical attention for good reasons. Although AI models might advance human welfare in unprecedented ways, progress will not occur without substantial risks. This article considers 3 such risks: system malfunctions, privacy protections, and consent to data repurposing. To meet these challenges, traditional risk managers will likely need to collaborate intensively with computer scientists, bioinformaticists, information technologists, and data privacy and security experts. This essay will speculate on the degree to which these AI risks might be embraced or dismissed by risk management.

Even as the U.S. Army attempts to integrate cutting edge technologies into its operations, many of its platforms remain fundamentally in the 20th century. The way tank crews operate their machine has gone essentially unchanged over the last 40 years. At a time when the military is obsessed with robotics, artificial intelligence and next generation networks, operating a tank relies entirely on manual inputs from highly trained operators. "Currently, tank crews use a very manual process to detect, identify and engage targets," explained Abrams Master Gunner Sgt. "Tank commanders and gunners are manually slewing, trying to detect targets using their sensors. Once they come across a target they have to manually select the ammunition that they're going to use to service that target, laz the target to get an accurate range to it, and a few other factors."

The U.S. Army will soon operate robots able to destroy enemy armored vehicles with anti-tank missiles, surveil warzones under heavy enemy fire and beam back identified targeting details in seconds due to rapid progress with several new armed robot programs. Several of the new platforms now operate with a Kongsberg-built first-of-its-kind wireless fire control architecture for a robotic armored turret with machine guns, Javelin Anti-Tank Missiles and robot-mounted 30mm cannon selected by the Army to arm its fast-emerging Robotic Combat Vehicles. These now-in-development robotic systems are intended to network with manned vehicles in high-risk combat operations. The fast-evolving concept is to optimize state-of-the-art networking between manned armored vehicles operating in a command and control capacity and forward-positioned armed robots capable of testing enemy defenses, performing surveillance under enemy fire or simply firing upon and destroying enemy targets when directed by humans. Made by Kongsberg, the MCT-30 turret is the first remotely-operated turret to be qualified and fielded in the United States, and a wireless fire-control has been demonstrated in ongoing testing.

The U.S. Air Force recently bought dozens of Chinese-made drones to use for testing and training, according to officials and records of the purchase, fueling concerns about continued Defense Department use of technology that lawmakers consider a threat to national security. The Air Force Special Operations Command, the service's highly trained commando division, bought 57 drones in September from Da-Jiang Innovations, or DJI, the world's largest maker of unmanned aerial systems, based in Shenzhen, China.

Artificial Intelligence, for most people, is a tech that powers chatbots or image recognition at best – basically, a software that tells images of cats from dogs. Others view it as a serious threat to their regular day jobs. Regardless of its impact on their lives, people view AI as a technology with tremendous future potential. While the future of AI elicits awe and fear, its impact on the present remains largely unacknowledged. From shortlisting resumes to spreading propaganda, AI is working harder on us than most of us know.

The U.S. Congress should create a federal agency for artificial intelligence. In 1906, in response to shocking reports about the disgusting conditions in U.S. meat-packing facilities, Congress created the Food and Drug Administration (FDA) to ensure safe and sanitary food production. In 1934, in the wake of the worst stock market crash in U.S. history, Congress created the Securities and Exchange Commission (SEC) to regulate capital markets. In 1970, as the nation became increasingly alarmed about the deterioration of the natural environment, Congress created the Environmental Protection Agency (EPA) to ensure cleaner skies and waters. When an entire field begins to create a broad set of challenges for the public, demanding thoughtful regulation, a proven governmental approach is to create a federal agency focused specifically on engaging with and managing that field.

Many projected that deepfake videos would play a lead role in the 2020 elections, with the prospect of foreign interference and disinformation campaigns looming large in the leadup to election day. Yet, if there has been a surprise in campaign tactics this cycle, it is that these AI-generated videos have played a very minor role, little more than a cameo (so far, at least). Deepfake videos are much more convincing today due to giant leaps in the field of Generative Adversarial Networks. These are generated videos that are doctored to alter reality, showing events or depicting speech that never happened. Because people tend to lend substantial credence to what they see and hear, deepfakes pose a very real danger.

The year 2020 continues to be difficult here on Earth, where the pandemic is exploding again in regions of the world that were once successful in containing it. Germany reported a record number of cases this week alongside Poland and the Czech Republic, as the U.S. counted 500,000 new cases. It's the backdrop to a tumultuous U.S. election, which experts fear will turn violent on election day. Meanwhile, Western and Southern states like Oregon, Washington, California, and Louisiana are reeling from historically destructive wildfires, severe droughts, and hurricanes. Things are calmer in outer space, where scientists are applying AI to make exciting new finds.

Early this spring as the pandemic began accelerating, AJ Venkatakrishnan took genetic data from 10,967 samples of the novel coronavirus and fed it into a machine. The Stanford-trained data scientist did not have a particular hypothesis, but he was hoping the artificial intelligence would pinpoint possible weaknesses that could be exploited to develop therapies. He was awed when the program reported back that the new virus appeared to have a snippet of DNA code -- "RRARSAS" -- distinct from its predecessor coronaviruses. This sequence, he learned, mimics a protein that helps the human body regulate salt and fluid balance. Venkatakrishnan, director of scientific research and partnerships at AI start-up Nference, wondered whether this change might allow the virus to act as a kind of Trojan horse. Could this explain its high infection and transmission rates?

Early this spring as the pandemic began accelerating, AJ Venkatakrishnan took genetic data from 10,967 samples of the novel coronavirus and fed it into a machine. The Stanford-trained data scientist did not have a particular hypothesis, but he was hoping the artificial intelligence would pinpoint possible weaknesses that could be exploited to develop therapies. He was awed when the program reported back that the new virus appeared to have a snippet of DNA code – "RRARSAS" – distinct from its predecessor coronaviruses. This sequence, he learned, mimics a protein that helps the human body regulate salt and fluid balance. Venkatakrishnan, director of scientific research and partnerships at AI start-up Nference, wondered whether this change might allow the virus to act as a kind of Trojan horse. Could this explain its high infection and transmission rates?