Today I am very excited to talk about something I know is a common question for many these days. It is something that I get asked a lot and what I know many see as the future of behavioral economics and the overall behavioral sciences: AI.  How can AI and machine learning work with behavioral economics to help with predictive models? Do they work together at all or are they at odds? Could the industry combine these things to be more effective? Sam Albert, Chief Digital Officer at Behaviorally is here to talk about these exact questions via their very cool tool called flash.ai.  Show Notes: [00:06] In today’s episode, I’m excited to introduce you to Sam Albert, Chief Digital Officer at Behaviorally. [02:50] Sam shares about himself, his background, and how he got into behavioral economics.  [04:48] PRS changed its name to Behaviorally back in January 2021. They are really trying to understand consumer behavior and help their clients make good decisions based on that behavior.  [06:45] Understanding how consumers are acting or reacting to certain stimuli in store and then what they tell you they actually would do or how they feel could be different. It is about lining those pieces up and telling one cohesive story that is going to essentially help clients to make good business decisions to move their businesses forward.  [08:44] Behavioral science can pretty much be applied to every aspect of our lives and it is happening unbeknownst to us in every decision every day.  [10:04] The industry is moving on this trajectory towards machine learning, more broadly leveraging AI. [10:44] They came up with a system called flash.ai. They are able to take their learnings and apply them so that the machine can learn how to mimic those behaviors.  [11:30] Their system applies image recognition. The machine reacts to the visuals in a similar way to what a human would do.  [12:39] This allows them to have a cohesive platform that takes into account all of the key pieces that really (from a behavioral standpoint) drive what consumers actually do in the market.  [13:09] The change to AI was already happening and COVID accelerated that change.  [15:00] The world is becoming increasingly more digital.  [16:53] They use a dynamic system where the existing work they are doing is feeding the future models that are being built. The models are continuously being updated to reflect the real world.  [18:32] They both validate the work to ensure it is accurate and the dynamic aspect of making sure the machine is keeping up with the pace of change in the world.  [19:08] Sam shares some of the case studies for flash.ai.  [20:14] If you don’t take the context around it into account, you put yourself in a position where you can either get false positives or false negatives and essentially give the wrong direction to clients. He is most proud of the system's ability to take context into account.  [21:36] Context and nuance makes a significant difference when you are talking about behavior in general.  [23:27] They see flash.ai tool as an earlier stage tool. Flash.ai allows them to test without spending the time, money, or energy to get real consumer feedback.  [25:46] Being different is important, but you don’t want to differentiate in ways that don’t help you stand out.  [27:01] Flash.ai is the first step and hopefully it siphons down the different options that would go into a full test. Then you can fully validate those and do any fine tuning you need.  [29:29] AI is not going away. It is just a matter of what it looks like in the future. The path to purchase is going to play a critical role in what we see in the future. [31:06] You can’t run away from technology. You just have to build it into what you are doing and leverage it. AI is going to play a pretty big role in that.  [33:15] There is a lot that is lost when you switch to a digital environment. However, looking at it as an opportunity, how could we make this an amazing experience for everybody in a