About This Discussion:
We’ve heard the stories that we should fear A.I, and that it’s going to take away all of our jobs, but what does a future with A.I. truly look like? In this episode, we were joined by Neil Sahota, IBM Master Inventor, UnitedNations A.I. Subject Matter Expert, and Author of Own the A.I. Revolution.
We dove deep into the future of A.I., and what we really need to be concerned about as this data starts to make important decisions. We also talked about the limitations of those decisions, and what we need to consider as this technology advances, and we talked about Emerging Technology and education through a standard university model. Is that really the right path to take for those who want to take on a career in these fields?
About Neil Sahota:
Neil Sahota (萨冠军) is an IBM Master Inventor, United Nations (UN) Artificial
Intelligence (AI) subject matter expert, and Faculty at UC Irvine. With 20+ years of
business experience, he works with clients and business partners to create next
generation products/solutions powered by emerging technology. He is also the
author of Own the A.I. Revolution, a practical guide to leveraging A.I. for social
good and business growth.
Neil’s work experience spans multiple industries including health care, life
sciences, retail, travel and transportation, energy and utilities, automotive,
telecommunications, media/communication, and government. Prior to his
current role, he was a thought leader, consultant, and practice leader in IBM
Global Business Services, where he led the sales and delivery of consulting
engagements in business strategy, new product development, revenue
optimization, process improvement, and business/system integration.
Neil has lived and worked in Ningbo, China, where he was involved in economic
development projects, gaining extensive experience in assisting companies
and entrepreneurs to define their products, establish their target markets,
and structure their companies. He is a member of several investor groups and
a director of various tech companies. Neil resides in California, and spends
significant time traveling the world to participate in business development and
global expansion projects.
Here is the official episode breakdown:
5:10 - We jump into Neil’s experience speaking in front of the UN along with hanging with Mike Tyson on his podcast to discuss which one was a scarier experience, and the misconceptions that the UN had about A.I. and what our future looked like.
6:24 - When it comes to working with these worldwide leaders, what level of education are they requiring to understand what the future looks like?
9:04 - People are fearful of A.I., and is that fear justified?
10:36 - We dive deeper into the applications of A.I. How exactly can we allow A.I. to make more in-depth decisions that would require a massive effort in coding?
13:58 - What’s the demand for data science as A.I. becomes better at making its own decision? Will data scientists eventually go away? Or will their roles become more important as A.I. advances?
16:28 - As we implement larger-scale efforts to analyze data, are there other initiatives to actually baseline the data?
18:08 - As a society that tends to be on the lazier side, how do we take initiative as a human race to work smarter than the robots?
23:40 - Teaching A.I. to grad students and applying it in the legal field and on the business side, including the future of work, how will that impact business moving forward?
24:02 - What is the definition of the future of work? What are jobs of the future going to be, and what are the skills that will be required to fulfill those jobs?
26:38 - How will the role of standard jobs change if A.I. is taking away some of the time that it takes the newbies to catch up to speed, almost like the grunt work (i.e. researchers in a law firm)?
28:30 - Is the curriculum for these Emerging Technology Courses advancing fast enough to align with the speed of change of the actual technology.
31:06 - Do we even need the training for these Emerging Technologies to happen in the standard university level?
36:15 - Is A.I. so advanced that they actually were able to get it to write Shakespeare?
38:23 - When it comes to A.I. and Social Media, is A.I. advanced enough to predict when posts may even go viral? How can companies use this data for the future?
40:25 - How do we protect ourselves from things like deep-fake when it comes to helping to make important decisions, for example, voting?
46:03 - We go back to the UN to discuss the new initiative that they have to help use A.I. for good.
Want to learn more about Neil? Visit
Twitter - https://twitter.com/neil_sahota
LinkedIn - https://www.linkedin.com/in/neilsahota/
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