How to Be a Better Human - TED Tech: Why people and AI make good business partners | Shervin Khodabandeh

Episode Date: September 26, 2022

What happens when the data-driven capabilities of AI are combined with human creativity and ingenuity? Shining a light on the opportunities this futuristic collaboration could bring to the workplace, AI expert Shervin Khodabandeh shares how to redesign companies so that people and machines can learn from each other. After the episode, TED Tech host Sherrell Dorsey dives deeper into the potential promises (and pitfalls) of AI-work integration. TED Tech is another podcast in the TED Audio Collective. To hear more ideas on the intersection of tech and humanity, follow TED Tech wherever you're listening to this. Hosted on Acast. See acast.com/privacy for more information.

The Apple Watch Series X is here. It has the biggest display ever. It's also the thinnest Apple Watch ever, making it even more comfortable on your wrist, whether you're running, swimming, or sleeping. And it's the fastest-charging Apple Watch, getting you 8 hours of charge in just 15 minutes. The Apple Watch Series X.

Available for the first time in glossy jet black aluminum. Compared to previous generations, iPhone XS or later required, charge time and actual results will vary. Hi, everyone. Chris Duffy here. We don't have a new episode of How to Be a Better Human for you this week, but we will be right back with new episodes next week. In the meantime, though, I wanted to share with you an episode of TED Tech. It's another podcast in the TED Audio Collective, and this one is hosted by tech journalist Sherelle

Dorsey. Every week, she explores a new idea at the intersection of humanity and technology. And we thought you'd particularly enjoy this episode. I know there can be a lot of robots will take our jobs kind of panic around. I feel that panic sometimes too. But this idea that Cheryl's talking about in this episode, it might just make you hopeful about what a positive collaboration for humanity and robots could look like. I hope you enjoy. And you can get more episodes by following TED Tech

wherever you're listening to this podcast. The robots are coming for our jobs. At least that's what a lot of people think. I wrote a book last year called Upper Hand, the future of work for the rest of us. And obviously, robots are going to be part of that future. But in the book, I said we can't be afraid of the robots. We'll need to work with them. robots, we'll need to work with them. We'll need more interdependence with robots and computers to become more efficient and ultimately to improve our own quality of life.

Welcome to the new TED Tech. I'm your new host, Sherelle Dorsey. I've worked for some of the country's leading tech companies, including Microsoft, Uber, Google Fiber, Trisata, and more. I founded and run a company of my own called The Plug. We offer news and insights into the trends shaping the future of work and business. I speak at Fortune 500 companies across the country, addressing big ideas about how we build the future together. And I coach on the power of inclusive innovation. These are the kinds of topics I'm really excited to go deeper on this season of TED Tech. All of which brings me back today to the future of work and artificial intelligence.

Back today to the future of work and artificial intelligence. The power of AI promises that AI will supercharge our business practices and admin tasks, predict our needs and outputs, manage customer service and optimize our supply chain and logistics. In my view, we've read, watched and listened to technologists opine about this utopian AI future, but we still have a long way to go to optimizing the way we use AI. AI expert Shervin Kodabande jumps into this on the TED stage, making the case for why AI makes for a good business partner. Stick around after the talk to hear more about the benefits and shortcomings of AI. ever. It's also the thinnest Apple Watch ever, making it even more comfortable on your wrist, whether you're running, swimming, or sleeping. And it's the fastest charging Apple Watch, getting you eight hours of charge in just 15 minutes. The Apple Watch Series 10,

available for the first time in glossy jet black aluminum. Compared to previous generations, iPhone XS or later required, Charge time and actual results will vary. I've been working in AI for most of my career, helping companies build artificial intelligence capabilities to improve their business, which is why I think what I'm about to tell you is quite shocking. Every year, thousands of companies across the world spend collectively tens of billions of dollars to build AI capabilities. But according to research my colleagues and I have done, only about 10% of these companies get any meaningful financial

impact from their investments. These 10% winners with AI have a secret. And their secret is not about fancy algorithms or sophisticated technology. It's something far more basic. It's how they get their people and AI to work together. Together, not against each other, not instead of each other. Together in a mutually beneficial relationship. Unfortunately, when most people think about AI, they think about the most extreme cases, that AI is here only to replace us or overtake our intelligence and make us unnecessary. But what I'm saying is that we don't seem to quite appreciate the huge opportunity that exists in the middle ground, where humans and AI come together to achieve outcomes that neither one could do alone on their own. Consider the game of chess. You probably knew that AI today

can beat any human grandmaster. But did you know that the combination of a human chess player and AI can beat not only any human, but also any machine. The combination is much more powerful than the sum of its parts. In a perfect combination, AI will do what it does best, which is dealing with massive amounts of data and solving complex problems. And humans do what we do best, using our creativity, our judgment, our empathy, our ethics, and our ability to compromise. For several years, my colleagues and I have studied and worked with hundreds of

winning companies who are successfully building these human-AI relationships. And what we've seen is quite interesting. First of all, these companies get five times more financial value than companies who use AI only to replace people. Most importantly, they have a happier workforce. Their employees are more proud, more fulfilled, they collaborate better with each other, and they're more effective. Five times more value and a happier workforce. So the question is, how do these companies do it? How do they achieve these symbiotic human-AI relationships? I have some answers.

First of all, they don't think of AI in the most extreme case only to replace humans. Instead, they look deep inside their organizations and at the various roles their people play, and they ask, how can AI make our people more fulfilled, more effective, more amplified? Let me give you an example. Humana is a healthcare company here in the US. It has pharmacy call centers where pharmacists work with patients over the phone. It's a job that requires a fair amount of empathy and humanity.

Humana has developed an AI system that listens to the pharmacist's conversation and picks up emotional and tone signals and then gives real-time suggestions to the pharmacist on how to improve the quality of that conversation. For example, it might say, slow down or pause or, hey, consider how the other person is feeling right now, all to improve the quality of that conversation. I'm pretty sure my wife would buy me one of these if she could, just to help me in some of my conversations with her. Turns out the pharmacists like it quite a lot too. They're more effective in their jobs, but they also learn something about themselves, their own behaviors and biases. Result has been more effective pharmacist and much higher customer satisfaction scores. Now, this is just one example of many possibilities where human AI collaborates. In this example, AI was a recommender. It didn't replace the human or make any decisions of its own. It simply made suggestions, and it was up to the person to decide and act. And at the

heart of it is a feedback loop, which, by the way, is very critical for any human-AI relationship. By that, I mean that in this example, first, I had to learn from humans the qualities that would make up a good or not so good conversation. And then over time, as AI builds more intelligence, it would be able to make suggestions. But it would be up to the person to decide and act. And if they didn't agree with the recommendation, because it might have not made sense to them, they didn't have to. In which case, AI might learn something and adapt for the future. It's basically open, frequent, two-way communication, like any couples therapist will tell you, is very important for any good relationship. Now, the key word here is relationship.

Think about your own personal relationships with other people. You don't have the same kind of relationship with your accountant or your boss or your spouse, do you? Well, I certainly hope not. And just like that, the right relationship between human and AI in a company is not a one-size-fits-all. And AI in a company is not a one-size-fits-all. So in the case of Humana, AI was a recommender, and human was decision-maker and actor. In some other examples, AI might be an evaluator, where human comes up with ideas or scenarios, and AI evaluates the complex implications and trade-offs of those ideas and makes it easy for humans to decide the best course of action.

In some other examples, AI might take a more creative role. It could be an illuminator, where it can take a complex problem and come up with potential solutions to that problem and illuminate some options that might have been impossible for humans to see. Let me give you another example. During the COVID pandemic, if you walked into a retail or grocery store, you saw that many retailers were struggling. Their shelves were empty, their suppliers were not able to fulfill the orders,

and with all the uncertainties of the pandemic, they simply had no idea how many people would be walking into what stores demanding what products. Now, to put this in perspective, this is a problem that's already quite hard when things are normal. Retailers have to predict demand for tens of thousands of products across thousands of locations and thousands of suppliers every day to manage and optimize their inventory. Add to that the uncertainties of COVID and the global supply chain disruptions, and this became a hundred times more difficult. And many retailers were simply paralyzed.

But there were a few who had built strong foundations with AI and the human AI feedback loop that we talked about. And these guys were able to navigate all this uncertainty much better than others. They used AI to analyze tens of billions of data points on consumer behavior and global supply chain disruptions and local government closures and mandates and traffic on highways and ocean freight lanes and many, many other factors and get a pretty good handle on what consumers in each unique area wanted the most, what would have been feasible, and for items that were not available, what substitutions could be made. But AI alone, without the human touch, wouldn't work either. There were ethical and economic trade-offs that had to be

considered. For example, deciding to bring in a product that didn't have a good margin for the retailer, but would really help support the local community at their time of need. After all, AI couldn't quite understand the uniquely human behavior of panic buying toilet paper or tens of gallons of liquor only to be used as hand sanitizer. It was the combination that was the key. And the winning companies know this. They also know that inside their companies, there's literally hundreds of these opportunities for human-AI combination, and they actively identify and pursue them. They think of AI as much more broadly a means to replace people. They look inside their organizations and reimagine how the biggest challenges and opportunities of their company can be addressed by the combination of human and AI.

And they put in place the right combination for each unique situation, and AI. And they put in place the right combination for each unique situation, whether it's the recommender or the evaluator or the illuminator or optimizer or many, many other ones. They build and evolve the feedback loops that we talked about. And finally, and most importantly, they don't just throw technology at it. In fact, this has been the biggest pitfall of companies who don't get their return from their AI investments. It's the over-investing technology expecting a piece of tech to solve all their problems. But there is no silver bullet. Technology and automation can only go so far, and for every one automation opportunity inside a company, there's literally 10 for collaboration. But collaboration is hard. It requires a new mindset and doing things differently than how we've always

done it. And the winning companies know this too, which is why they don't just invest in technology, but so much more on human factors, on their people, on training and re-skilling and re-imagining how their people and AI work together in new ways. Inside these companies, it's not just machines replacing humans. It's machines and humans working together, learning from each other. And when that happens, the organization's overall rate of learning increases, which in turn makes the company much more agile, much more resilient, ready to adapt and take on any challenge. It is the human touch that will bring the best out of AI. Thank you. The Apple Watch Series 10 is here. It has the biggest display ever.

It's also the thinnest Apple Watch ever, making it even more comfortable on your wrist, whether you're running, swimming, or sleeping. And it's the fastest-charging Apple Watch, getting you eight hours of charge in just 15 minutes. The Apple Watch Series 10. Available for the first time in glossy jet black aluminum. Compared to previous generations, iPhone Xs are later required.

Charge time and actual results will vary. Shervin Kodabande clearly outlines the opportunities and the limitations of ethical AI. outlines the opportunities and the limitations of ethical AI. These limitations have been highlighted by many women researchers and technologists in the field as well, like Drs. Joy Boulamwini, Safiya Younobl, Timnit Gebru, Ruha Benjamin, and Kathy O'Neill. Because of their diverse backgrounds, such researchers have had a unique view into how the mindless use of AI can actually have pointed downsides, particularly on vulnerable populations and communities of color. These impacts should not be taken lightly. One glaring example is how facial recognition software is notoriously bad at identifying Black people.

recognition software is notoriously bad at identifying Black people. This can lead to police misidentifying Black people and imprisoning them for crimes they didn't commit. Other algorithmic technologies may target ads toward users of certain demographics over others based on race or income data. For example, real estate ads have targeted certain demographics over others, resulting in what we call digital redlining. In other words, keeping people of color out of certain neighborhoods. To enable better AI practices in business,

we can look to companies that have began hiring social workers on their development teams. Companies like Facebook and Microsoft and others. Collaborations between engineers and social workers will become increasingly important as AI becomes a bigger part of our lives. We'll need those collaborations to make more equitable and human-centered algorithms, ultimately building a much more equitable tech landscape. Business leaders today have the ability to leverage AI to make the day-to-day seamless, but making room for humans

to poke holes in potential harmful outcomes will make AI deployment more intentional. There's still much to learn, but we don't have to be afraid of the robots. We just have to find the places where humans and robots intersect in productive ways. Places where AI can correct for our worst human impulses. Places where AI can correct for our worst human impulses. And places where humans can gain real, meaningful efficiencies from AI without further damaging vulnerable populations in the process. I'm Sherelle Dorsey, and this is TED Tech. In the episodes ahead, we'll keep digging into the future.

Join me next week for more. The Apple Watch Series 10 is here. It has the biggest display ever. It's also the thinnest Apple Watch ever, making it even more comfortable on your wrist, whether you're running, swimming, or sleeping. And it's the fastest-charging Apple Watch, getting you 8 hours of charge in just 15 minutes.

The Apple Watch Series X. Available for the first time in glossy jet black aluminum. Compared to previous generations, iPhone XS or later required, charge time and actual results will vary.