Dr. Lia DiBello is the Chief Science Officer of ACSILabs, Inc, which makes the FutureView Platform — a virtual reality training platform used by the US military and by certain large businesses to accelerate expertise. I last talked to Lia about her groundbreaking work explicating the mental model of business expertise, and in fact created this podcast to interview her. She’s back today to talk about her use of AI to accelerate expertise.
Neil Sahota is the CEO of ACSILabs. Neil was part of the original IBM Watson team that won the Jeopardy challenge. After that challenge, he was, amongst things, the person responsible for IBM’s Watson ecosystem strategy, and an IBM Master Inventor (which is a designation for IBM employees who have made outstanding contributions to the IP creation process at IBM). Since leaving Big Blue, Neil has been Artificial Intelligence Advisor to the United Nations, published a book about AI in 2019, and started the UN’s AI For Good Initiative, which is currently hosted under the International Telecommunications Union.
In this episode, we take a human-first perspective on using and deploying AI in real world business and military contexts. We discuss Lia and Neil’s history with AI, talk about good and bad implementations of AI they’ve seen in real-world environments, and discuss what it means to get more folks to an expert-level at human-AI symbiosis.
Shownotes
ASCI Labs — https://acsilabs.org/
ASCI Labs in the Navy STP marketplace — https://acsilabs.org/acsi-labs-has-met-the-requirements-to-be-listed-in-the-navy-stp-virtual-transition-marketplace/
AIQ (Artificial Intelligence Quotient): Helping People Get Smart about the Smart Machines They Are Using — https://medium.com/about-work/helping-people-get-smart-about-smart-machines-they-are-using-f9e0095846fe
AIQ: Artificial Intelligence Quotient — https://www.psychologytoday.com/us/blog/seeing-what-others-dont/202007/aiq-artificial-intelligence-quotient
Hoffman, R.R., Mueller, S.T., Klein, G., & Litman, J. (2018). "Metrics for Explainable AI: Challenges and Prospects." Technical Report, Explainable AI Program, DARPA, Washington, DC. — https://arxiv.org/abs/1812.04608
Timestamps