AI also has the potential to affect plenty of other industries, the medical industry is a good example. Let’s say you go to the doctor for a skin abnormality. The programs that decide if it is benign or malignant have the ability to be hacked and altered in a way that would give inaccurate readings to the doctors. This poses a threat to our health as well as a possible unnecessary financial burden as medical bills can cost a small fortune. Moreover, this issue could be applied to many other industries, not just the medical field,

Another major issue with AI is Adversarial Attacks. Adversarial Attacks are issues with the inputs that go into the Machine Learner model that the attacker uses to to cause the program to make a mistake. These attacks pose a major problem to AI products as a small, unintentional issue, has the ability to completely alter how the computer works. For example, by placing just two stickers on a stop sign, a self-driving car read the sign as a 45mph speed sign, instead of a stop sign. Clearly, this poses major safety issues to the occupants of the car, as well as everyone on the road.

Another example of racism and bias in self driving cars is their ability to detect white pedestrians much more accurately than black pedestrians. And it wasn’t even close. The comparison suggests that a white person was “10% more likely to be correctly identified as a pedestrian than a black person”. The Georgia Institute of Technology went on to state that they found a bias in the self-driving car’s system where they are less likely to spot an African American pedestrian on the street. Again, this poses a serious safety threat to many pedestrians, as well as uncovers and issue with AI and how ethical it all is.

By providing AI with as much infomation as we can, and not just include our own views, AI will be better able to identify people of all races and be abke to understand small differences, such as a sticker on a stop sign.