Levi, Ray & Shoup, Inc.

The role of ethics in AI

3/25/2021 by Steve Cavolick

By Steve Cavolick

The loss of a loved one is always painful. A common lament heard after the passing of a relative or close friend is, “I wish I would have told them (insert that thing here) …”

At some point in the near future, you may be able to communicate with the dead and share all of those thoughts with them whenever you like. Microsoft was granted a patent in December of 2020 for AI technology that could create a chatbot based on a “past or present entity ... such as a friend, a relative, an acquaintance, a celebrity, a fictional character, a historical figure.”

The technology would need to first collect social media posts, images, voice data, electronic communications (texts and emails), and even written letters from the person you wanted to talk to. After indexing the content, the conversational chatbot model would be trained to converse like the person. The bot could also be linked to outside sources to comment on topics that aren’t included in the person’s indexed digital history.

My first reaction was that this could be awesome. But the more I thought about, I decided I would not want this because it isn’t that person. An informal poll of family and friends resulted in 100% of them saying they would take a pass if it was an actual product. Feedback included comments such as, “That’s creepy,” and “It might be comforting at first, but not for the long term.”

Creep factor aside, this also raises the question around the ethical use of data and AI models. In this case, is it ok to use all of a deceased person’s data to create a “living” avatar if they did not give you permission to? Will we have to edit our wills to include statements about the use of our personal data once we’re gone?

We all agree data sharing can be helpful. Who doesn’t love receiving a relevant offer based on things we’ve browsed for or previously purchased? But our digital actions and images are being captured everywhere we go, sometimes without our consent or knowledge. As AI becomes more ingrained in our lives, there are ways to make sure it benefits individuals and improves the performance of companies without jeopardizing privacy and using learned bias:

  • Recognize that ethics needs to play a role in AI. If you are building AI applications, establish a committee that includes members from your company, outside industry experts, and academia, among others, to understand the implications of using your algorithms.
  • Implement review processes on how you use training data and what the outputs are.
  • Establish a governance organization to monitor and ensure that AI is deployed in an ethical manner.
  • Seek diversity among technologists to remove bias.
  • Make transparency of AI algorithms a requirement. No black boxes. Trust and acceptance of your models will grow if you can explain how they come to the decisions and outcomes they do.
  • Educate technical teams on the ethics of AI algorithms and data usage.

No matter where you are on your journey to AI, the trustability and traceability of your data and predictive models are foundational characteristics of analytical best practices.

If you have already built AI applications and would like to understand how the LRS Data Science team can help you govern them, we can help. If you’re not quite there yet, the LRS Big Data and Analytics group has over 20 years of experience implementing applications in advanced analytics, information management, and data warehousing. Not sure how to get started? Our strategic offerings can help you align business and technology teams, discover the right use case, and determine an ROI. If you are interested in understanding how we can help you find value in your data, please fill out the form below to request a meeting.

About the author

Steve Cavolick is a Senior Solution Architect with LRS IT Solutions. With over 20 years of experience in enterprise business analytics and information management, Steve is 100% focused on helping customers find value in their data to drive better business outcomes. Using technologies from best-of-breed vendors, he has created solutions for the retail, telco, manufacturing, distribution, financial services, gaming, and insurance industries.