How is artificial intelligence affecting business leaders? Revolutionizing the workforce? The future of efficiency and profit?
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Alexander Ferguson 0:00
Welcome to UpTech Report. What is artificial intelligence or AI? In this third topical episode, we’ll explore what are specific use cases and challenges for AI in business? And how might it revolutionize the workforce? In the coming years? To help answer these questions, we’ve interviewed a whole panel of AI experts, business leaders, CEOs, and entrepreneurs who are applying AI in their business today. So we asked our experts, what else can ai do for business?
Richard Boyd 0:32
I would start with like, let’s look at all the little things that you do today that we can have an assistant do for you. And apply it there first. But of course, it can do a lot more than that
Chris Hazard 0:44
thinks it today, you’re encountering AI a lot more than you realize. You just don’t believe you know, the types of advertisement you’re being served the, you know, where things are stocking the shelves, or some specific stores. Like there’s a lot of behind the scenes things, optimizing supply lines, or supply chains, I should say that they’re impacting people without them really knowing
Richard Boyd 1:09
fights, we ramble around the internet, we leave little cookies and little behavioral patterns around behind us of like, what were we interested in? You know, Google is tracking? You know, where do we go on the internet? Which pages? How long do you stay at each page? And that ends up being a creating an interesting model around like, what are your real interests,
Alicia Klinefelter 1:31
that’s actually one of the biggest applications. And I think it’s not just Facebook, you know, anyone who’s getting revenue from advertisements is definitely utilizing machine learning a couple of
Mason Levy 1:41
things, and you’ve got a really powerful as your cloud service that’s going to be providing intelligence to your system. And that could be for product recommendations, it could be for natural language processing, it could be for image recognition, if you want to build that into your application or service. You know, those those kind of core frameworks, again, are there,
Robbie Allen 2:00
you know, another one that’s that you probably heard about is resume analysis. So can you automatically scan a resume and then tell me if that person is going to be potentially a good employee for me or not,
Jeff Lerose 2:10
we’ve seen a lot of situations where you can train people to do their jobs, through AI and gamification. And on the simplest level, it’s leaderboards and seeing how people are performing against their group or their peers. It also allows you to find out what people are good at, and what they’re not good at, okay, and how we can get them to learn a lot quicker what technologies work for the learning what techniques work for the learning,
Robbie Allen 2:42
everybody has a different use case. And the reason for that is we’re so early on in the machine learning journey, that there’s not just one or two applications of it, in fact, you go into a large company, and there’s dozens of applications of it. And so right now, because people are just getting started, no two companies tend to have the exact same need or the exact same priority. Because machine learning is a real sort of general purpose tool that you can apply to lots of problems.
Alexander Ferguson 3:08
Clearly, AI has plenty of effective uses for different types of businesses. But how has AI changed the fundamental approach for business leaders?
Alicia Klinefelter 3:19
For me, I see it more as a revolution of finally having enough compute power, essentially, to do a lot of these complex algorithms that you know, have been limiting this revolution for years, if you’ve
Rett Crocker 3:30
got a business case where you’re trying to predict how much your customers going to spend next year, or whether or not customer x is going to like something or not. Those are great uses for AI because you’re basically saying, I’ve got a bunch of data that shows how people have reacted in the past. I’m going to use that to try and predict the future,
Richard Boyd 3:48
always thinking about how do you apply automation to solve business problems so that you can scale provide better experiences. And, you know, ultimately, these things are a lot smarter than us is assuming that the data that’s within the data set is tagged properly, etc. So,
where more and more things are automated. And and if I’m a young person today, I would look at the career I’m going to choose and think like how susceptible is that activity to being automated?
Alexander Ferguson 4:19
Our experts agree that automation can help businesses become more efficient. That poses an obvious question, a potential concern for employees and employers alike. Will increased use of aI mean fewer jobs? How exactly will AI affect the future of the workforce? Our experts weigh in
Rett Crocker 4:40
the right future for us is one where the AI’s of the world are basically aiding us and allowing us to do not have to do that grunt work. And instead, we’re doing all the stuff that really requires a big brain.
Robbie Allen 4:52
No, a lot of the jobs that I see that maybe are going to go away in the near term, their jobs that we shouldn’t have people doing them, the only reason we have people doing that because we didn’t have technology before, we
Mason Levy 5:01
had the Industrial Revolution, which was automation of industrial industrial tasks. And, you know, yes, it replaced people who replaced jobs. But the great thing is, is at every point in history, when we’ve had things that automated tasks, new jobs were created higher level jobs, better paying jobs, in order
Robbie Allen 5:20
to have machine learning, working in a real world environment. And in a production setting, you need somebody that’s kind of keeping an eye on it over time, you need somebody that’s helping keeping it trained over time, I refer to those as machine learning assistants. And so for all the jobs that are going to go away, because maybe somebody is doing a very routine manual task, there’s a new set of jobs that are going to open up to helping keep the machine learning algorithms trained over time,
Mason Levy 5:44
if you have a third to fifth grade reading level, and you can identify baby elephants in a photo and box it, you know, you’re going to be okay in this. And so it’s not like you need a data science, computer science degree from from Harvard or Stanford in order to to accomplish these objectives here business.
Alexander Ferguson 6:03
We’ve heard a lot about the benefits of AI. But what challenges do business leaders face with AI and machine learning, we asked our experts.
Robbie Allen 6:13
It all starts with data. And that’s what we tell every client with machine learning is it all starts with your data. The root of most of the problems when it comes to applying machine learning comes from the issues with data,
Rett Crocker 6:25
I think that most people that are doing AI are using not enough data. And it is going to result in incorrect, incorrect conclusions. And we’re going to have bad results. And there’s there’s a potential, particularly on the consumer side of things where the bar is higher for people to get turned off by some of the API’s that we’re building. And I think it’s incumbent on us to get it right.
Robbie Allen 7:02
Machine learning, as I mentioned, is learning patterns and data. And if the data has garbage in it, or if it’s very noisy, or there’s problems, especially ones that you don’t anticipate, or you can’t see yourself, then the algorithm is going to learn those those you know, learn that noise, or it’s going to start making Miss judgments because it’s learned patterns that were incorrect. And so if the data is not in pretty good shape, you’re gonna have problems.
Alexander Ferguson 7:25
Of course, not every business leader is familiar with using AI and machine learning. And our final question, we asked our experts, what advice they would give to those looking to better utilize AI in their field.
Mason Levy 7:39
If you’re a small business owner, or even a large corporation that’s looking to get into AI, it doesn’t have to be, you know, $100,000 or a million dollar investment. Really the simplest, the easiest way to start is to Mechanical Turk and fake it, right. And so your decision tree things and make sure that the data tagged properly, so that later somewhere down the road, you can start to implement, you know, actual machine learning and, and data science on top of it. You know, just having your data structured properly, is a huge challenge for a lot of businesses just to overcome and understand.
Richard Boyd 8:18
And I think every organization, every government, every person, again, should be thinking about every activity they’re involved in and thinking what should machines be doing? And what should humans I would
Mason Levy 8:29
say, a lot of companies, their core competency is not building artificial intelligence systems, right? Their core competency is some domain topic, right? I’m really great at healthcare. And I’m going to continue to be really great at healthcare. And so maybe I’m going to partner with somebody that can help build an AI system, where I’m bringing expertise to that AI system in order to perform some type of inaction.
Chris Hazard 8:55
I would say that that AI right now, it’s very easy to overhype it, and also very easy to dismiss it. And the right path is somewhere between to understand it understand how can use in your industry, how it can be applied and what results you’re likely to see and make sure that you can understand why the decisions are being made.
Alexander Ferguson 9:12
That concludes the audio version of this episode. To see the original and more visit our UpTech Report YouTube channel. If you know a tech company, we should interview you can nominate them at UpTech report.com. Or if you just prefer to listen, make sure you’re subscribed to this series on Apple podcasts, Spotify or your favorite podcasting app.