Moving past FOMO : building an AI strategy with Garik Tate

“Humans should move from fear to curiosity about AI in a business setting and relinquish control in certain areas”

A great conversation with Garik about AI strategy and what it means for businesses – how they can leverage AI for business outcomes and the value it can bring to people in the business. We delve into myths on what it can and cannot do, and how leaders can think about what AI means for them and their organisations.

AI is based on explicit language to build up intelligence but is only as good as the data it is given; it acts like a type of mirror, giving impressions and reflections of the data fed into it. As with anything new, people fear the cutting edge but there will be lots of new opportunities and jobs in an AI world, and stepping over fear and doing it anyway is the path to creativity.

Leaders should talk to people throughout the organisation to canvas opinion and start with ‘non-exotic’ use of AI to simply improve the lives of employees. A culture of adoption for AI can be scaled by channelling or eliminating fear to enhance the human mind because we must be at our best/most creative to deal with AI technology.

Garik shares his insights, thought leadership and experience on the subject of AI and the human dimension of technology.

The main insights you’ll get from this episode are :

–       ‘Programming is teaching the dumbest thing in the world how to be smart’ (Gabe Newell). AI is based on explicit language to build up intelligence but is only as good as the data it is given; it acts like a type of mirror, giving impressions and reflections of the data fed into it.

–       Data is the starting point, but AI strategies involve scientific, engineering, regulatory, and business breakthroughs / cycles – democratising intelligence offers massive opportunities for entrepreneurs to take advantage of technology.

–       Well-built systems with added AI will offer huge increases in productivity and there is a trend towards mass personalisation/customisation – lots of new tools are being rolled out with seismic effect.

–       At present, AI is like a newly qualified, well-educated, hard-working personal assistant; a brainstorming partner and creative asset that only works with very clear inputs and outputs and does not fare well with lack of context.

–       The better questions we ask, the better answers we will get, and great expertise is required to ask great questions – it is not about indiscriminate learning.

–       Humans should move from fear to curiosity about AI in a business setting and relinquish control in certain areas – this requires intention and discipline about what we input.

–       Open source is very cheap as a means to test the best output – there is an understandable fear of sharing information, but the open AI API does not use your data as training data; it does not record data and can be viewed more as an AI playground for personal use.

–       Practical AI is embedded in business by building a culture of adoption, generating excitement and creating a story – not to replace humans but to enhance them. Custom instructions and internal databases can be created to meet company-specific requirements – they can be tested first and then used without requiring human input.

–       Up-/side-skilling in terms of an adoption culture must be on a case-by-case basis – it is difficult to add AI to blue collar work (cf. Moravec’s paradox). And reality is infinitely complex and therefore the human brain takes shortcuts – abstract thoughts only work in a vacuum, not in the real world.

–       A culture of adoption for AI can be scaled by channelling or eliminating fear to enhance the human mind because we must be at our best/most creative to deal with AI technology – this also compares to other types of transformation that require leading by example, explaining the vision and rewarding progress.

–       The culture of AI can be scaled by people understanding the environment or what’s not being said and using their life experience to articulate using their voice and eyes. Engage people by recruiting champions who want to step up; introduce AI as a ‘research project’; facilitate empowered, decentralised decision-making.

–       People fear the cutting edge but there will be lots of new opportunities and jobs in an AI world, and stepping over fear and doing it anyway is the path to creativity. Leaders should talk to people throughout the organisation to canvas opinion and start with ‘non-exotic’ use of AI to simply improve the lives of workers.

Find out more about Garik and his work here :

https://www.linkedin.com/in/garik-tate/?originalSubdomain=ph

https://www.valhalla.team/

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Suzie Lewis

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