Many scholars and educators argue the antidote to some of the ethical problems with artificial intelligence (AI) is to integrate ethics and AI or embed ethics in AI.2,12,14 The product of this combining is supposed to lead to Ethical AI, a term that is both frequently used and seemingly elusive.5,9,13 Although attempts to make AI ethical are to be lauded, too little attention has been given to what it means to "integrate" or "embed," be it integrating ethics and AI or embedding ethics in AI. A rather simple idea of additivity seems to be behind these proposals. That is, the efforts are directed toward figuring out how ethical principles can be "injected into"11 AI or how an ethical dimension can be "added to" machines1 or, if the focus is on the latest wave of machine learning, how to "teach" machines to act in an ethical way.10

Over the past several years, concerns around AI ethics have gone mainstream. The concerns, and the outcomes everyone wants to avoid, are largely agreed upon and well documented. No one wants to push out discriminatory or biased AI. No one wants to be the object of a lawsuit or regulatory investigation for violations of privacy. But once we've all agreed that biased, black box, privacy-violating AI is bad, where do we go from here?

As you read this, AI systems and algorithmic technologies are being embedded and scaled far more quickly than existing governance frameworks (i.e., the rules of the road) are evolving. While it is clear that AI systems offer opportunities across various areas of life, what amounts to a responsible perspective on their ethics and governance is yet to be realized. This should be setting off alarm bells across society. The current inability of actors to meaningfully address AI ethics has created a perfect storm: one in which AI is exacerbating existing inequalities while simultaneously creating new systemic issues at a rapid pace. But why hasn't this issue been effectively addressed?

We live in a world fundamentally transformed by our own creations. Once imagined only in science fiction, artificial intelligence now powers much of the technology we interact with every day--from smart home devices to cognitive assistants to media recommenders. While subtle by design, the impact of AI is far-reaching. The field of education is no less affected by these technologies. AI shows up in instructional chatbots, personalized learning systems and administrative tools.

Colby College is a private liberal arts school located in southern Maine. You can take classes in art history, chemistry, music, all the staples, and now the school is adding artificial intelligence to the list. Colby is among the first liberal arts colleges to create an artificial intelligence institute to teach students about AI and machine learning through the lenses of subjects like history, gender studies and biology. The college received a $30 million gift from a former student to set up its new institute. This, of course, comes as the world is grappling with ethics and AI and how to build a moral foundation into algorithms.

TechRepublic's Karen Roby spoke with David Crandall, assistant professor of computer science at Indiana University about artificial intelligence (AI), computer vision, and the effects of the pandemic on higher education. The following is an edited transcript of their conversation. David Crandall: I'm a computer scientist, and I work on the algorithms, the technologies underneath AI. And I work, specifically, in machine learning and computer vision. Computer vision is the area that tries to get cameras that are able to see the world in the way that people do, and that, then, could power a lot of different AI technologies, from robotics to autonomous vehicles, to many other things.

At the perfect intersection of technology and civil service, every government process will be an automated one, streamlining benefits, outcomes, and applications for every citizen within a digitally-enabled country. With that approach comes a significant layer of protocol that is necessary to ensure citizens feel empowered regarding decision-making processes and how their government addresses needs from a digital perspective. Right now, Canada is leading the world in AI, thanks largely to huge government investments like the Pan-Canadian Artificial Intelligence Strategy. The growing field is pervasive right now--there is hardly an industry it has not disrupted, from mining to legal aid. In fact, government might be one of the most obvious choices as to where automated decision processes can save time and money.

The starting point for any discussion about AI will almost certainly focus on how we should use it, and the advantages and disadvantages it could bring. Google's Sundar Pichai recently suggested AI could be used to help solve human problems -- a noble goal. How we use it to solve these problems, and ultimately how successfully they will be, is going to depend on our ethics. A machine learning algorithm can't tell you whether a decision is ethical or not. It's going to be up to human creators to imbue machines with our own sense of ethics, but it's not so easy just code in the difference between right and wrong.