One issue that is not receiving enough attention is that of cyberattacks evolving from being performed by humans against other humans through the use of technology, to computers attacking computers, with little human involvement. Another important AI and cybersecurity concern is that AI systems can be hacked by feeding them bad data from which to learn – the systems themselves do not need to be compromised to render them impotent or worse. The first is to prevent the AI from making incorrect observations and decisions because it suffers from a lack of complete data, or biased data, for the matters which it is supposed to address. Ensuring that systems are created and tested by diverse teams, as well as that during learning phases systems are fed sufficiently diverse data, can help address such concerns. The second issue is that AIs may make decisions that society views as inappropriately biased, but which the AI considers being both correct and integral to achieving maximum performance.