AI is being developed extensively to serve a multitude of purposes, yet a crucial aspect often neglected in discussions pertains to the individuals who may be marginalized by these advancements. Our guest today, Matt Smith, co-founder of Speak to Family, addresses this very concern by creating technology specifically aimed at enhancing communication for aging adults who frequently encounter barriers in digital fluency. This episode delves into the ethical implications of AI, emphasizing the need for thoughtful, human-centered design that prioritizes the needs of the elderly rather than simply catering to the technologically adept. Through our conversation, we explore how ill-conceived applications of AI can inadvertently perpetuate biases, particularly against those who are often excluded from the conversation. Join us as we investigate the intersection of technology and humanity, and consider how we might bridge the gap for those who are most vulnerable in our society.

The discourse presented within this episode revolves around the burgeoning field of artificial intelligence (AI) and its pervasive implementation across various sectors, often neglecting a critical demographic: the elderly. Many discussions typically center on the most advanced and disruptive technological advancements, yet this conversation seeks to illuminate the voices that are often marginalized in such narratives. The episode features an insightful dialogue with Matt Smith, co-founder and head of product at Speak to Family, a company dedicated to creating user-friendly communication tools aimed specifically at bridging the gap between aging adults and their families or caregivers. Matt’s personal experiences, particularly regarding his mother’s challenges with technology, serve as the impetus for this innovative venture, emphasizing that ethical technology should cater to all, especially those who are often overlooked in the tech conversation. The episode delves into the ethical considerations surrounding AI, urging listeners to contemplate not only the functionality of AI applications but also the moral implications of their deployment, particularly concerning inclusivity and accessibility for aging individuals who may struggle with digital fluency. Matt articulates a vision of AI that prioritizes meaningful connections rather than mere technological prowess, advocating for solutions that genuinely address the needs of marginalized communities, thus redefining what it means for technology to be ethical and inclusive.

Takeaways:

• The current landscape of artificial intelligence is characterized by widespread development across various sectors aiming to address diverse needs.
• Discussions surrounding artificial intelligence often focus on the most advanced and disruptive technologies, overlooking significant ethical implications.
• It is crucial to consider the needs of marginalized populations, particularly those lacking technological fluency, such as elderly individuals.
• The ethical deployment of AI necessitates a careful assessment of its necessity and potential biases that may arise from its application.
• The Speak to Family initiative exemplifies how technology can bridge communication gaps for aging adults who may be isolated due to their inability to navigate modern devices.
• The core challenge in aging technology lies in aligning investor expectations for rapid returns with the slower adoption rates inherent in the aging demographic.

Links referenced in this episode:

• speaktofamily.com

Companies mentioned in this episode:

• Speak to Family
• Amazon Alexa

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Dear listeners, AI is being built everywhere right now by everyone, for almost every conceivable purpose.

And most of the conversation around it focuses on the cutting edge, the most capable, the most powerful, the most disruptive version of the technology.

But here's the catch.

There's a quieter question that doesn't get nearly enough attention.

Like what about the people who are most likely to be left out of that conversation?

The elderly parent who cannot figure out a smartphone.

The aging adult who is isolated not because they want to be, but because the tools we have built assume a level of dignity, fluence, digital fluency, they were never given.

So today's guest is building AI for that person.

And what he's building says something important about what ethical technology actually looks like in practice.

Yes.

So, hey, dear listeners, welcome back to another powerful episode of Mind Meets Machine where we explore what happens when human values meet the technology reshaping our world.

I'm your hosta Vega and I'm really glad that all of you here today and my guest today is the co founder and head of the product at Speak to Family.

Speak to Family, a purpose driven company building elegantly simple voice and digital communication tools to bridge the gap between aging adults and their families, caregivers and communities.

So he is a technology entrepreneur, strategic thinker, and someone who has staked his work on the belief that most meaningful applications of AI are not always the most glamorous ones.

Right.

So I'll not take much of your time.

To listeners, let's get started.

Welcome to the show, Matt.

Matt Smith.

Thank you.

Very happy to be here.

Thanks.

Amazing, Amazing.

So, Matt, like before we get into the ethical AI and everything that you are building, I want to start with the origin of Speak to Family.

Most technology entrepreneurs build for the most connected, the most digitally fluent, the easiest market to reach.

Right.

So you choose the opposite one.

So what was the personal moment that made that bridging?

Yeah, like a lot of people in htech, it came from a personal need.

My mother was a little disconnected from technology back in the day.

We would all call her on the phone and talk to her, just live.

But as texting and social media became more popular, we ended up, you know, talking more to each other on those platforms and less to my mother directly.

So we just started to see her get a little more isolated and just out of the loop.

So she was really the first customer, was just building a little prototype for her so that she could text and get messages using an Amazon Alexa device.

And in that way she didn't have to learn how to use an app or tap or swipe, she could just speak and it was very effective for her.

So, you know, one thing led to another and it turned into a company.

What we found was just that there are so many marginalized people in society that people are not building products for, but who are very valuable and really should be staying connected just as much as anyone else.

So my personal experience led to us building speak too.

Amazing.

Yeah.

And so if we bring this word, like the misconception, ethical AI is definitely the phrase that gets used a lot of right now and sometimes meaningfully, sometimes as a kind of branding exercise.

According to you, what's the most, I'd say core misconception about the ethical AI actually requires that you find most prevalent in the technology industry.

Yeah.

So the ethics around AI are, I mean, they're not really happening right now.

So, you know, we've tried to take an approach and promote an approach around AI to really consider some ethical aspects of it up front early.

So first and foremost, you know, are you applying AI for a really good reason or are you applying AI because you just feel like everything should have AI connected to it at this point?

So, I mean, just something simple like, you know, you know, I'm presenting content to someone, do I really need to present to them the option of summarizing the content that they're already seeing, you know, using AI?

So we see a lot with emails, right?

Email comes across and there's a button that says, do you want me to summarize this email?

I mean, hopefully the email is clear and summarized enough that I don't need AI to do that for me.

So some of the decision is just where should I apply AI in an ethical way that it's actually helpful to the user and not just a frivolous use of AI?

And the reason that's ethical is there's a lot of compute power, there's a lot of impact on the environment, there's a lot that goes behind and underneath AI that impacts all of us.

So the more we use AI, the more that impact happens.

And there's just sort of an ethical concept around, you know, maybe using this only where it's needed.

The other piece of it is just there's a lot of bias in AI and to try to identify bias and ensure that your product is working in a way that is not perpetuating bias or introducing a new bias.

All of the AI engines are taking in everything they could possibly take in right now.

So every time you press that button to do a summary you're feeding the AI engines more information.

And all of that has some bias built into it.

So it's AI is based on our previous knowledge and our previous content and all the things that have been happened before, which is inherently has some bias built into it, socioeconomic, you know, political, whatever it might be.

So when we go to summarize something, especially with what we do, where we're caring for people who are aging, we have to be really careful to make sure that we're not applying a bias of the wrong demographic to a summary for someone who might be in a different demographic.

So the demographics and the bias that's built into the content, especially with generative AI, we have to be really cautious of that.

So when we're building out our model, we're taking into account where that bias may take place and how to actually address that bias when we're delivering new content.

So just simple things like that, should I even be using AI and is the AI biased?

I think are two really simple ways to apply some ethics to what's going on with AI right now.

I agree, I agree.

And yeah, exactly.

I mean, and in the context of your specific work, like building for aging adults, for people who may have the cognitive decline, for families, navigating caregiving, what does the ethical AI mean in concrete?

Like, and what decisions did you have to make in building speak to family that a less ethically grounded product would not have met?

Yeah, I mean, it's, it's really subtle things that you just have to watch out for.

So one of the things that we're doing more of now is, you know, taking in things about someone and trying to figure out what we can do best to support their wellness.

So we might understand someone's hobbies, someone's past, you know, things that they did in the past with their education, what their professional life might have been.

And you take all that in and you kind of build a profile of someone to say what kind of events are they most interested in?

What other residents might they be most social with?

So we can make connections and introductions, how do we inform their families about their wellness and their activity?

So if you look at all that, what you're basically saying is, I'm profiling someone, I'm trying to get personal information from them and then I'm going to use that information to make their lives better.

Right.

But in any situation, there's a double edged sword to that, which is I am getting a profile.

And theoretically that profile could be used to target someone, to purchase something to, you know, Tell them what they may or may not like.

And sometimes those things can be inaccurate.

And if you're not careful about how you present that to people, it can.

It can go down a bad path.

So as an example, someone might say they really like, you know, they like sports, they like, you know, football, they like baseball, and they like live events.

So you might come back from that and say, hey, I have a great idea.

You should go to the baseball game tomorrow night at the local stadium.

But that person might have some other things that prevent them from being able to do that, whether it be economic, physical.

They don't have any way to actually facilitate that recommendation.

We shouldn't be recommending something to someone without understanding all of that information.

So even just identifying what might we be missing about someone, especially someone aging, are they mobile?

You cannot make a recommendation for someone to participate in an event that requires mobility if the person is just not mobile.

So before you make that recommendation, you have to have that kind of check in place.

Most of the generative AI is not going to do that.

You have to feed them a full profile and then hope for the best results.

So with our model, we're building that into the actual recommendation engine is there are certain checks and balances you have to have to someone who's aging.

And those things can change very rapidly.

Within six months, someone might become immobile, or they might have an injury, or they might be on a new medication.

So these things have to be real time, and your model has to be flexible enough to identify those things in real time.

So you're making the appropriate recommendations.

Exactly.

I totally agree.

And, you know, like, isolation among aging adults is one of the most significant and least discussed public health crisis that we have.

Right.

So it is associated with the cognitive decline, the physical health deteriorations, and significantly shortened lives.

So what is the technology gap that is contributing to that isolation, if you can share.

Yeah, well, it's interesting.

So you mentioned cognitive decline.

I mean, I think you have to start with what does that actually mean?

Right.

So cognitive decline might.

Someone might seem like they're having cognitive decline to someone, and it might just be that it's taking them a little bit longer to respond to something or something about their health is making them, you know, their hearing may not be what it used to be, so it takes them a little more time to process something.

And that's not necessarily cognitive decline.

Right.

The understanding is there, the acuity is where you'd want it to be, but it might be interpreted as cognitive decline.

So I think, you know, you start with that sort of thing.

But to your point about the technology itself, most technology is not designed for someone who's aging.

Right.

It's designed for your typical consumer, you know, 18 to 24 or 18 to 35 people.

People who are consuming technology are typically viewed as being on the younger side.

So when apps are being built, when websites are being built, the things that we all use to get content and to, you know, sign up for a ride to get an Uber or whatever it might be, they're all designed for people who are, who are younger.

So, you know, that's where we have to start, is the design of a product can actually make someone more isolated because it wasn't designed for them.

And if it's not designed for someone, they're not going to use it as much.

When they do use it, it looks to the outside world that they don't know how to use it or they can't do it, which perpetuates the cycle.

Right.

So I think one of the big things that we would love to see more often is maybe different versions or accessibility versions of apps that take into account someone who's aging, who may just need larger fonts, larger buttons, more contrast in the user experience.

And you know, those supposed cognitive declines might not even be there.

It might just be that the design is not intended for someone in a certain demographic.

That's interesting.

Yep.

And I mean, AI specific role in this.

Right.

Like, because what you are building is not just a simplified phone or a kind of messaging app.

AI is doing something in the background.

So what is actually doing that a non AI solution could not accomplish?

Yeah.

So I mean, to be fair, you know, not all aspects of our product are, have any AI in them.

I mean, we started building our product before this whole AI revolution happened.

There's a lot of just traditional technology in our platform where we've applied AI a really two areas.

One is in our UI design.

You can hear my, my AI assistant talking to me now.

Exactly.

Yeah, we, we have.

Please come to that.

That's a, that's a great way.

Also, like we can help people also understand like things are working at the background as well.

Right.

So.

Yeah, yeah, well, I have, I have my, my demo assistant right here.

But basically what, what I was saying is that we don't necessarily have a ton of AI in our code yet, but what we're doing more with AI is making the effectiveness of the interaction of the user more measurable.

So we can now take all the data that we're gathering, whether it Be people asking for help, people asking for content, people trying to connect the dots between what events do I have and what's, what's on my calendar.

We can take all that and look at that and use AI to tell us how we can be more effective on how we're servicing our clients.

So we are using some co generative AI as well, so we can build things faster, so we can get things to market faster.

And I think almost everybody must be doing that at this point.

But where we're seeing the most value with AI is looking at our data and telling us where are we most effective, where are our clients most effective?

What content is resonating most with clients, what events are, are resonating most with our clients, and then sharing that back with our client base and saying, hey, based on everything we're seeing, we're able to deduce a lot of these trends and get it back to you.

So you know what's more effective?

That's, that's incredible because in the past people would just have sort of just reports and you would look at reports and graphs and a lot of that had to be manual and had to be interpreted.

Whereas with AI we can take a lot of that same data and present it back to people and make it actionable much faster and much more clean than it was maybe even six months or a year ago.

I agree.

And like building technology, obviously for a population that the mainstream industry ignores means you are often solving problems that don't have existing playbooks, don't have well funded competitors to learn from, and don't have the investors lining up with the conviction.

Right.

So what has been the hardest part of this journey?

Like not the technical challenges, but the human and the strategic ones.

Yeah, there's more interest in aging technology, the H tech space than there was even just a few years ago.

So the, especially in the United States, the aging population is exploding.

There's a stat, you know, 10,000 people a day turn 65.

So the baby boomer generation are aging into retirement.

It's very wealthy demographic.

So there's more and more, you know, resources being put into that space.

The longevity economy, so to speak, where, where we've run into, I think the problem, the conflict comes where people who invest in software and invest in technology tend to be looking for a return in a specific period of time that is not realistic in the aging space.

So for example, just using round numbers, if you raise a million dollars in HTEC, you know, most VCs or investors within two or three years, they're going to want to see a 10x return on that.

Right.

So they want to see $10 million in growth within the next two or three years.

The industry that we're dealing with does not have that kind of rapid adoption.

You know, you come out with a product, it's not like you're going to scale up and everyone's going to start buying it and paying for it immediately.

It takes some time.

So I think that's the biggest disconnect is the money is looking for a quick turnaround like they would in a consumer space or in a more traditional investment environment.

Whereas in the aging space it's just not that rapid, it's not that fast of a turnaround.

So there's a disconnect between the investment community and the technology community.

And typically what happens is the technology community, the vendors, they want to get the money so that they can go execute.

So they get the money based on some conditions that are not reachable and they're just bound to meet with some level of challenge along the way.

So I think that's, that's what we've seen speak to our company.

We're independently financed, so we have not raised money in that capacity, which has been really good for us because it's allowed us to grow slowly and to really focus on product market fit rather than having investors tell us, hey, you have to hit these numbers by these dates.

So we've been very fortunate in that way.

But I know a lot of other companies have not had that same benefit.

I agree.

I totally agree.

Yeah.

And, and also like, so this is for the listeners who are listening right now and who has an aging parent or grandparent.

They are not as connected as the want to be.

I mean, who keeps meaning to call but doesn't senses the window closing but doesn't know what to do with that feeling.

So what would you want them to hear right now?

Yeah, I mean a lot of this is just a human problem and family problem and societal problem.

And I don't know that technology can really solve that.

I think the one thing that we are trying to do at Speak to is to meet people where they are.

So, you know, 15 year old grandson of, you know, someone who's 85 years old, that 15 year old is probably not going to pick up the phone and call grandma.

Yeah, you know, they don't pick up the phone and call anyone.

They're using text, they're using social media or they're texting.

And just phone calls are less popular than they were with, you know, with the younger generation.

So what we try to do is connect.

You know, grandma who wants a phone call is not getting it, 15 year old is not making the phone call.

But there can be a messaging app that actually works for both of them where the 15 year old can send a picture, maybe do a little video, send it off to grandma, and grandma sees it on a tablet, or grandma sees it on her TV and can respond from the tv.

And now grandma is using a very familiar piece of technology, her TV and her remote.

And you know, 15 year old is just using their app.

So that's what we're trying to do is connect people and meet them where they are, regardless of their demographic.

You know, one demographic might be on tv, one might be on a tablet, one might be using an Alexa, one might be using a phone.

And by connecting all of those dots, now we have an ecosystem that can actually communicate with each other effectively.

Removing those barriers of technology is actually not talking to each other.

Exactly.

And if you have to give one advice to all the listeners, what that will be.

I think the one piece of advice I would give, you know, trying to stay on the, on topic, is to just to look at how you can help each other stay connected and to not think that people as they age don't care about staying connected or can't do something.

I think people who are aging are far more capable than younger people give them credit for.

I think because the physical manifestation of aging might appear to be slower, confused, you know, maybe it seems like this person just can't do something.

I think when you give people who are aging the chance and you educate them a little bit and you give them the time to learn, they're very willing to learn and very willing to do things that are challenging because no one stops wanting to learn, no one stops wanting to communicate, no one stops wanting to be challenged, no matter how whatever age you are.

So that's my piece of advice is when you see someone aging, don't assume that they can't do something.

Assume that they can and they just need help.

And Matt, like if someone wants to connect with you, what would be the great way of to connect?

So the easiest way to find me is on our website, Speak to family.

Com.

So it's Speak with the number two.

This is our logo and family.

Com I'm on there, my partner's on there.

It's hard to find me with the name Matt Smith.

It's kind of hard to find me otherwise.

You can find me on LinkedIn again if you search Matt Smith on LinkedIn along with speak to.

You'll find me.

And I'm always happy to get back to people if anybody wants to talk more about any of these topics.

I'm always interested to talk to everyone.

And dear listeners, what I have to say is like what I'll do is I'll put all the links and dedicates into the show notes for you.

Easy reference so that you can easily reach out to Matt.

And with this, I have to say that that's the wrap for today's episode on Mind Beats Machine.

And if this conversation made you think about someone in your life who might be more isolated than you'd realize, please don't let that through.

Pass act on it today.

A call, a message, a visit.

The window is always narrower than we think.

So as I said, maths details will be there in the show notes.

And if someone in your world is caring for an aging adult and struggling with the communication gap, then please share this with them.

With this this is your host, Avik, and this is mindmitsmash.

The most human thing I can do is to help us be more human with all of us.

So take care of yourselves and the people that you love the most.

So see you next time.

Thank you so much.