A Robot with a Heart: The Unexpected Intersection of AI and Empathy
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A Robot with a Heart: The Unexpected Intersection of AI and Empathy

It's not your imagination: AI is having a moment.

Conversations that started out with AI being a method to reduce cost and cut jobs, have become discussions on the way AI can make all of us more effective and creative.

But Monifa Porter , Mach49's SVP and leader of Shift AI, goes one step further. Her bold query: Can AI boost human empathy?

The time to start is now. Enjoy.

By Elke Boogert, Mach49 Managing Editor


A Robot with a Heart: The Unexpected Intersection of AI and Empathy

By Monifa Porter , SVP and Head of Shift AI

Can machines teach us how to care? I think so. In fact, our future might hinge on machines deepening human empathy.

AI is everywhere. On the news. In your newsfeed. In the boardroom. Every big company seems to be in a rush to integrate AI into their operations, often to lessen the need for human input. For instance, when top executives discuss AI, they often ask, “How can we use AI to reduce human costs?” (This translates to “job cuts”). A recent forecast suggested that 10 million Americans would need to learn new skills after AI takes over their jobs. So, it's not shocking that the average person links Artificial Intelligence with apprehension and fear.

I can ask a whole host of wild, rhetorical questions about the possibilities of AI outside of efficiencies and laying off people, but I’ll get straight to the point:

What if, by teaming up with entrepreneurs globally, AI could be used to gain a better understanding of — and deeper empathy for — human beings??

One of the biggest hurdles many companies, big and small, face is gathering enough detailed information about current and potential customers to make informed decisions. Companies must understand their customers — who they are and what matters most to them — in detail. What high priority problems can a company solve for its customers? Businesses shell out hundreds of billions of dollars each year trying to collect or purchase profile information. Sadly, they often fail to gather more than a superficial snapshot of those individuals.

Take the example of two American men: both are Gen X, both married with children. Their estimated personal wealth is over $70 million, and they both have an interest in basketball, music, and politics. Seems like a lot of info, right? You can deduce a lot from these traits, right?

Wrong. Both former President Obama and rapper Ice Cube fall into this category — and they couldn't be more different.

This is why companies struggle, even with large databases of customer records.

The numbers are too small, woefully incomplete, and they offer only limited help in characterizing potential new customers.

AI can help overcome constraints in complexity and sample size. Mach49 has over ten years of venture building experience. As part of our venture incubation process, we’ve interviewed hundreds of potential customers per venture. Over the last decade, that's tens of thousands of in-depth customer interviews. We crafted a series of AI prompts to elicit the kinds of insights that we gleaned in these interviews: What are the highest priority pains that customers are experiencing? Which value propositions resonate most, relative to those pains? Which products or features do customers think will best deliver on the promises of those value propositions?

We compared AI responses to these prompts, to the data from real human interviews — anonymized, of course — and found that our AI “customer doubles” matched those human responses with stunning accuracy.?

Imagine you want to create an app that would help people lose weight. The immediate challenge is that many people want to lose weight, for a variety of reasons. Some people want to lose weight for a range of immediate medical reasons; others want to prevent future health problems; still others want to change their appearance. That's only the beginning because any weight loss plan needs to recognize differences in lifestyles, culture, age, and weight goals. The task at hand is to pinpoint all these individual "pain points" and provide solutions to the biggest of them.

That's a lot of complexity, produced by an enormous combination of variables. With traditional market analysis, coming up with these combinations — much less implementing solutions for them — would take years and enormous amounts of capital.

Yet, this is exactly where AI excels.

Its greatest strength is its ability to dig deep, establishing a body of data that can then be mixed and matched into millions of different configurations.

In trying to describe the impressive ability of AI to create responses that mirror the detailed idiosyncratic needs, desires, and preferences of customers, I've settled on a very human term: empathy. The ability to put ourselves into the lives of others. It may sound strange, but as we conducted this experiment and built AI “customer doubles,” we learned that Artificial Intelligence can have a kind of empathy too.

Empathetic AI could be a game changer in almost every industry

  • ?In healthcare, empathetic AI assistants could offer emotional support, spot signs of depression or anxiety, and gently nudge people to seek help;
  • In education, AI tutors that get when students are frustrated could adjust their teaching methods to keep learners engaged;
  • In customer service, companies could create empathetic chatbots that pick up on cues like irritation or delight and adjust their responses, making interactions feel more human.

I believe that AI may prove to be our ultimate assistant, due its uncanny ability to improve products and services. Through empathy, AI can ensure services become less expensive, more personalized, and more precisely suited to our needs. At the deepest human level imaginable.

Monifa Porter, SVP and Head of Shift AI

MONIFA PORTER is at the helm of Shift AI, a groundbreaking Mach49 venture providing a platform of AI products.?Monifa’s career spans from Fintech to Adtech to IOT. At Paypal, her team’s pioneering work in fraud detection used algorithmic approaches to risk analysis, applying regression modeling techniques to real-world applications. At Adchemy, she patented products that applied NLP and machine learning to solve complex advertising optimization challenges. At Opower, Monifa led an IOT thermostat startup within a startup, delivering energy efficiency to customers’ homes through behavioral science-driven interactions that predicted energy costs and influenced behavior to lower them. At Taulia, she led a large organization spanning product, design, compliance and data science. At AAA, Monifa stood up an innovation lab, bringing “Silicon Valley inside.”

Monifa lectures at her alma mater, the Stanford Graduate School of Business, on Product Management. Monifa, her daughter, and her partner have also cultivated a flourishing permaculture garden at their home, playing their small part in the “unbreaking” and re-making of our planet.


Opportunities Disguised as Big Hairy Problems

Our weekly list of must-read media, curated by Rich Karlgaard, on emergent "Chief Officer" titles, bitter disappointment and unregulated AI. In short, opportunities disguised as big hairy problems.

How last year's imperfect season led to South Carolina's perfect title / By Michael Voepel / ESPN / April 7

Reason to read: Learn what South Carolina’s coach, Dawn Staley, did to overcome last year’s bitter disappointment to create what basketball experts believe is the top women’s team ever and a potential generational franchise. Questions to ask: Defeat and failure in business (as in sports) are inevitable, especially in “risk on” venture growth projects. Successful organizations learn from the losses, adapt quickly, and move forward with both realism and optimism. Is your company a fast learner and adapter, or does it get stuck in blame and defeatism?


AI Is Moving Faster Than Attempts to Regulate It. Here’s How Companies Are Coping / By Isabelle Bousquette / The Wall Street Journal / March 27

Reason to read: Learn how Nationwide Mutual Insurance established a “red team, blue team” approach. “The blue team explores new AI opportunities and the red team considering where it should pull back due to concerns around cybersecurity, bias and ensuring it can meet government regulation,” writes the author. Question to ask: Amid the fog of uncertainty about AI regulation in your industry and countries of operation, what are you doing to move ahead?


The C-suite is expanding — and IT leaders are stepping up / By Esther Shein / CIO Views Magazine / April 8

Reason to read: Rapid and successful deployment of AI tools will require new team skills and leaders. Learn why Chief [Experience, AI, Transformation and Sustainability] Officers are emergent positions and might be right for your company. Questions to ask: How is your company organizing for successful AI and GenAI adoption? Are new “chief officer” titles required, or will that just create more overhead and bureaucracy?


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Growth Igniter | Servant Leadership | Building Community Eco-systems to Thrive | ElderCare | Disability | Longevity | Customer Journey | Customer Experience

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