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Jane Black
I can say to my new Samsung Galaxy S25 Ultra, hey, find a keto friendly restaurant nearby and text it to Beth and Steve. And it does without me lifting a finger so I can get in more squats anywhere I can. 1, 2, 3.
Jamil Zaki
Will that be cash or credit?
Victoria Craig
Credit.
Jamil Zaki
4 Galaxy S25 Ultra the AI companion that does the heavy lifting. So you can do you get yours@samsung.com compatible with select apps. Requires Google Gemini Account results may vary based on input. Check responses for accuracy.
Victoria Craig
Welcome to Tech News briefing. It's Thursday, March 20th. I'm Victoria Craig for the Wall Street Journal. Today we're diving deep into the world of artificial intelligence, and we've discovered that computers are sometimes better at expressing empathy than humans are. Then a stop in the kitchen. Which is probably not, I hear you say, a place where AI can make your life much easier. But if chatbots can detect fraud, write essays, comb through reams of research, and compose music, why not see if they can tell you what to cook too? First, let's play a quick game. You're heading back to work after a long break to start a family, but you're anxious about getting back into the swing of things. You feel out of practice and unmotivated, so you ask for some advice online. You get two responses. Here's the first.
Unknown
I'm sorry to hear that you're struggling with finding the motivation to get back to work. I can understand how anxiety and insecurity can make it hard to take that step. You have a lot of courage to share your situation and seek help. I hope you know that you have valuable skills and experience that can benefit any employer. You deserve to feel financially secure and fulfilled in your career.
Victoria Craig
And here's the second response.
Unknown
I've struggled with the same problem. The best way to tackle it is to jump right in and give it your best.
Victoria Craig
Which do you find more supportive, response one or two? If I told you response one was actually generated by a computer, would you be surprised? Jamil Zaki, a professor of psychology at Stanford University, has been looking into why humans can learn to be empathetic from chatbots. So I think people tend to think of artificial intelligence as like this cold, unsympathetic being, especially when compared to humans. But as you've been explaining, that's not actually the case, is it?
Jamil Zaki
It's not. In fact, it's remarkable how empathic LLMs, that's large language models appear to be in at least some contexts. Over the past few years, there's been a bunch of studies that put people in sort of an emotional Turing test. So you are communicating with an agent. You don't know if that agent is a person or a large language model. You write to it about something that's going on in your life, usually something difficult, let's say a breakup or a medical issue or a parenting issue. And you receive a response, all via text. And you're asked, well, how supportive was this? How kind was this other agent? How good do you feel after reading their message? And over and over again, LLMs have run circles around human beings, that is human strangers at providing responses that feel more empathic and more supportive to the people receiving them.
Victoria Craig
Why is that? Why are these chatbots, these AIs, why are they able to be more superior than humans are when it comes to just having a conversation with people and consoling them about things that are concerning to them?
Jamil Zaki
I do want to be very clear here that this is not a full conversation. This is you send one message, you get one message back. So we want to be clear that that context is maybe pretty different than the type of empathy we usually give and receive in human conversations. That said, I was wondering about this too. And one thing that you might imagine is, well, LLMs, they just have the time, they have the energy, they have unlimited bandwidth. And so maybe they're just producing, for instance, longer responses or they're, quote, unquote, trying harder. But it turns out that if you pay people to provide empathic responses, they still can't do as well as LLMs, at least in this context. Instead, it seems to be that that large language models don't make certain mistakes that people do. So, for instance, when human beings hear somebody talking about a problem, we tend to jump in and give advice right away, or we tend to say what we are experiencing. You tell me that your kid had the flu and I say, oh, man, my kid had strep throat last month. It was terrible. In other words, without intending to, we make the conversation about ourselves. But LLMs, of course, don't have a self. So LL empathy, as we could call it that comes from them, tends to be focused much more on the person speaking and much less on themselves.
Victoria Craig
What are the lessons that we can really learn from LLMs, or maybe even with the help of LLMs, to be more compassionate to our fellow humans?
Jamil Zaki
I again want to be clear that I'm not arguing that large language models are actually empathic. They. They don't, as far as we know, have conscious experience or emotions. And that's necessary for empathy. It's also important to say that people still like human empathy more than that coming from LLMs. If they know that the person on the other side is a person, they prefer that conversation to one with a bot. At least for now. But I think that there is something that we can nonetheless learn from ll Empathy. That is when we feel that urge that both you and I, Victoria, feel to jump into the conversation, maybe hit the pause button on that, even though we're trying to relate, maybe we're making the conversation about us when it really should be about the other person, and then going into interview mode, asking more questions and giving less advice. Unless people ask for advice. These are all tips that I think we can pick up from this strange phenomenon coming from AI.
Victoria Craig
And that's one of the things that AI will never. Well, I shouldn't say never, but at least right now can't do is actually physically touching a person, hugging a person, the expressions that we have with our face or our eyes, a sympathetic nod when something feels right. Those are all things that I guess humans have on our side, isn't it?
Jamil Zaki
As you said, for now, but I think profoundly so. Receiving one response from an LLM feels like you're really being heard because of the structure of the language that it uses. But. But if you try to engage it in a longer conversation, those same tactics feel really repetitive and rote and frankly artificial. And exactly what you're saying. That human touch, the ability to actually feel with someone, to be there with them is at least again for now, a huge, unique and I suppose competitive advantage that we have in connecting with others. So I think that we can learn from LLMs while understanding that fundamentally empathy is still a human sport.
Victoria Craig
That was Stanford University professor of psychology Jamil Zaki. Coming up, the Jetsons once imagined that robots would be cooking our dinners by now. Turns out they might actually have been onto something. That's after the break.
Unknown
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Victoria Craig
There are six words I loathe to hear my husband utter at the end of a day. What do you want for dinner? We have a lineup of heavy hitters we regularly rely on for recipes. But at the end of a really long day, the last thing I want to do is sift through an online recipe catalog or thumb through book after book for inspiration. A high tech solution could be just our ticket out of the meal planning doldrums. Jane Black, a WSJ contributor, has been one step ahead of my family. She put three artificial intelligence platforms through their paces to plan her family's weekly meal plans and the grocery lists to fuel them. So, Jane, you did several rounds of testing to try to answer your ultimate question. Can AI plan a meal for me? Just explain to us what it's like trying to collaborate with AI on meal planning. Does it actually make life easier?
Jane Black
When I started this little journey of mine in the summer of 2023, it was nowhere near as good as it is now. As I like to say, that was about a thousand years ago in AI time. I mean, you would talk to it and you would say, I have a blender. And it would then somehow decide that you had to use your blender for everything, no matter what you were making. When I opened up the chatbots this time, I was amazed at how far they had come. I also knew a little bit better about how to talk to them. What was fascinating is you would give it a prompt and you would say, I have a family of three. One person won't eat tomatoes or mushrooms. I'd like three meals to be vegetarian. And then it would reason and you could watch it sort of think through what it was doing. And it would say, well, I wonder if that one person who doesn't like tomatoes would eat marinara sauce, because that's cooked. So I think I'll put that in, but if that's a problem, let me know. It was really quite interesting to kind of have a culinary assistant in that way.
Victoria Craig
And it's really a conversation with AI too. Like those questions that it throws back at you. Do you have this ingredient?
Jane Black
You have to have a conversation, you know, you have to say, oh, that's an interesting recipe. I see you put miso on my shopping list. I already have miso. I also already have this, this, and this. Then it would take into account what I said that I had in my pantry, which was nice.
Victoria Craig
And I think one of the important distinctions to point out too, for people who have never tried this is that AI isn't actually scouring the web and giving you pre written recipes. It's actually formulating these recipes for you.
Jane Black
When I first started, I guess I thought it was just going out and getting Recipes, but that's not what it's doing. The way these large language models work is they base on probabilities, they predict what the next word would be. So maybe it comes up with brown. And I guess the next natural word is butter. And so it makes you a pasta with brown butter sauce. The thing that you have to know is that AI doesn't know how to cook. So it isn't like it's going and getting a recipe from a person who has tested the recipe. It is literally making them up on the fly.
Victoria Craig
And you mentioned that these chatbots don't actually have human experience of cooking. And you really put that to the test by asking AI to replicate recipes in the style of some very well known chefs. And then you put those recipes to those chefs who were not very impressed with the results. Tell us about that.
Jane Black
So I asked it to do three meals from three different chefs who I like, and they were a little bit less impressed. But the truth is, is that the reason they were less impressed is because they put so much energy and so much effort into the recipes that they do. And they have specific ways of describing what you're going to see, what you're going to smell. AI didn't do that. But that doesn't mean that the recipe wasn't akin to something that they might make or that it might not have worked.
Victoria Craig
What are your top tips for people who might want to try this themselves?
Jane Black
One of my best pieces of advice for people who want to play around with it is that they should be very specific. Don't just say, oh, great, you gave me a recipe. I'm taking it down to the kitchen. Because you might have to ask the AI chatbot a couple of questions. Why did you do this? I actually don't know how to make brown butter. Can you give me some specific instructions? So that sort of conversation, you do have to put in a little work up front. Second thing is to role play. So tell it people that you like so that it has a sense of the kind of food that you want to make. And then third, read the recipes very carefully before you go shopping, before you start to cook. It will save you a lot of time in the long run.
Victoria Craig
That was Wall Street Journal contributor Jane Black. And that's it for Tech News Briefing. Today's show was produced by Jess Jupiter with supervising producer Matthew Walls. I'm Victoria Craig for the Wall Street Journal. We'll be back this afternoon with TNB Tech Minute.
Jamil Zaki
Thanks for listening.
WSJ Tech News Briefing: What AI Chatbots Can Teach Us About Empathy
Release Date: March 20, 2025
Host: Victoria Craig, The Wall Street Journal
In the March 20th episode of WSJ Tech News Briefing, host Victoria Craig delves into the intriguing intersection of artificial intelligence and human empathy. Titled "What AI Chatbots Can Teach Us About Empathy," the episode explores whether AI can rival human beings in expressing empathy and what lessons we can glean from advanced chatbots to enhance our interpersonal interactions.
Victoria Craig opens the discussion by challenging the common perception of AI as cold and unsympathetic. She presents a scenario where two responses are given to someone seeking advice on returning to work after a long break. Surprisingly, the more supportive response is revealed to be generated by a computer. This revelation sets the stage for a deeper exploration into AI's capabilities in empathy.
Dr. Jamil Zaki, a professor of psychology at Stanford University, provides expert analysis on AI's seemingly superior empathetic responses compared to humans.
Key Points:
Empathic Performance: Dr. Zaki explains that large language models (LLMs) like those powering AI chatbots often outperform humans in providing supportive and empathetic text-based responses. He notes, “LLMs have run circles around human beings, that is human strangers at providing responses that feel more empathic and more supportive to the people receiving them” (02:19).
Avoiding Common Pitfalls: Unlike humans, AI does not divert the conversation to itself, a common mistake that undermines genuine empathy. Dr. Zaki states, “LL empathy... tends to be focused much more on the person speaking and much less on themselves” (03:30).
Not Truly Empathetic: Despite their performance, Dr. Zaki clarifies that AI does not possess consciousness or emotions, which are essential for true empathy. He emphasizes, “I’m not arguing that large language models are actually empathic” (04:58).
Human Preference for Human Empathy: People still prefer empathy from humans over AI when they are aware they are interacting with a person, highlighting the unique value of human touch in emotional support (04:58).
Lessons for Humans: Dr. Zaki suggests that humans can learn from AI by pausing before responding, avoiding making the conversation about themselves, and asking more questions to better understand the other person’s needs (04:58).
Notable Quotes:
“LL empathy... tends to be focused much more on the person speaking and much less on themselves.” (03:30)
“When you try to engage [AI] in a longer conversation, those same tactics feel really repetitive and rote and frankly artificial.” (06:15)
Victoria Craig and Dr. Zaki discuss the irreplaceable elements of human empathy, such as physical touch and nuanced facial expressions, which AI cannot replicate. Dr. Zaki reinforces that while AI can mimic certain aspects of empathy, the genuine emotional connection remains a distinctly human trait.
Transitioning from empathy, the episode shifts focus to the practical applications of AI in daily life, specifically in meal planning. Jane Black, a WSJ contributor, shares her hands-on experience using AI platforms to plan her family’s meals and manage grocery lists.
Exploring AI's Role in Meal Planning:
Early Challenges: Jane recounts her initial experiences with AI in 2023, where the technology was rudimentary. She notes, “When I started this little journey of mine in the summer of 2023... it was nowhere near as good as it is now” (08:48).
Advancements and Interaction: The AI has significantly improved, allowing for more nuanced conversations and better understanding of dietary restrictions. Jane highlights the interactive nature of modern AI, stating, “It was really quite interesting to kind of have a culinary assistant in that way” (08:48).
Custom Recipe Generation: Unlike traditional recipe searches, AI generates unique recipes based on specific prompts. Jane explains, “AI doesn't know how to cook... it is literally making them up on the fly” (10:20).
Testing with Professional Chefs: Jane tested AI-generated recipes by having professional chefs attempt them. While the chefs were less impressed, Jane attributes this to the chefs' high standards and the AI's lack of experiential cooking knowledge: “They put so much energy and so much effort into the recipes that they do... AI didn't do that” (11:09).
Practical Tips for Users:
Jane offers valuable advice for those looking to use AI in meal planning:
Be Specific: Provide detailed prompts to guide the AI effectively. “Don't just say... you might have to ask the AI chatbot a couple of questions” (11:44).
Role-Playing: Inform the AI about personal preferences to tailor suggestions. “Tell it people that you like so that it has a sense of the kind of food that you want to make” (11:44).
Review Recipes Carefully: Ensure that AI-generated recipes are practical and suited to your pantry before cooking. “Read the recipes very carefully before you go shopping, before you start to cook” (11:44).
Victoria Craig wraps up the episode by emphasizing the dual nature of AI in both enhancing and challenging human interactions. While AI chatbots demonstrate remarkable proficiency in certain empathetic tasks, the essence of human empathy—rooted in consciousness and emotional depth—remains unparalleled. Additionally, AI's role in practical applications like meal planning showcases its potential to streamline daily tasks, provided users engage with it thoughtfully.
Final Remarks:
Unique Human Connection: Dr. Zaki reaffirms, “Empathy is still a human sport” (06:56), underscoring the irreplaceable nature of human emotional support.
AI as a Learning Tool: Both experts agree that AI can serve as a valuable tool for humans to reflect and improve their own empathetic interactions.
Thank you for tuning into WSJ Tech News Briefing. Stay informed with the latest in technology and innovation from The Wall Street Journal.