Leaders Shaping the Digital Landscape
May 26, 2023

WorkWave: Surfing the Digital Tides

Have you ever wondered what the future of work will look like in the coming years with the AI rollercoaster rumbling in? You are not alone. Let's find out this coming Friday in the conversation that host  will hold with , Chief Digital...

Have you ever wondered what the future of work will look like in the coming years with the AI rollercoaster rumbling in? You are not alone.

Let's find out this coming Friday in the conversation that host Tullio Siragusa will hold with Piyush Malik, Chief Digital & Transformation Officer of Veridic Solutions, centered around one of the hottest topics of the year: navigating the future of work in the AI-powered Era.

You don't want to miss this one! Save the date.

#ai #artificialintelligence #futureofwork #futureofwork2023 #workplacetechnology

Transcript

Tullio Siragusa (00:12):

Happy Friday everyone. This is Tullio Siragusa with Tech Leaders Unplugged. I'm getting unplugged today with Piyush Malik, who's the Chief Digital and Transformation Officer at Verdict. Good to, excuse me. Good to have you with me this morning or this afternoon, this evening, wherever you are watching us. It's good to have you. We're talking about the topic, of today's Workwave: Surfing the Digital Tide. I really love how that flows off your tongue, you know, work wave, serving the digital tide. And we're talking about navigating the future of work in the AI-powered era. This is a very interesting topic indeed. Let's see what we can learn today. But before we do, let's get to know our guests a little bit. If you could Piyush let us know how you got here. How did you get to this journey, what has that been like, and what does your company do?

Piyush Malik (01:12):

Well, wonderful to be here. Thank you for having me on your show, Tullio. I came to the U.S. 27 years ago as an immigrant on H1B Visa like a lot of folks in the dot com era. And prior to that Y2K era came here to take care of a lot of things on the technology side. I cut my teeth in management consulting after my engineering and product management jobs. And then I got into Price Waterhouse Coopers. Then we got acquired by IBM. And I thought I'll be there only for a few years. And fast forward 20 plus years I was traveling all around the world building teams in business intelligence and analytics work, and serving clients all around the world. And then the startup bug hit me after one failed startup and one successful exit. I'm onto this, my third startup, so-called startup. It's a 300-person company where we focus on digital transformation and helping clients get onto their AI-driven journey. Throughout my entire professional career, I have been educating the use of data for decision-making and helping clients and companies reach their objectives using, using the principles of data first and analytics first. And then all along the way we have seen the resurgence of AI again and again. And we'll talk more about it. But that's in a nutshell how I got in here with my education back in India, and then professional experience around the world.

Tullio Siragusa (03:08):

Excellent. You brought back some memories. You were APWCC. I was at the regular PWC where we were working on that deal with IMP. So you brought back some memories. So, anyway, let's go right into the topic that we're discussing today. And that is the concept of a workwave. What is that about? Tell us a little bit more.

Piyush Malik (03:33):

So, as I was alluding to earlier we've been surfing the AI wave lately, and especially since November 2022, when ChatGPT became a household dinner item conversation. But I've been there before that in the AI real if you will. Back in 2011 IBM created a wave of cognitive computing when the IBM Watson system defeated two human champions, the longest serving champion human champions in the game of Jeopardy. Now, that was, of course, used to create a little bit of noise in the market, but at the same time, it captured the imagination of folks. And a lot of people got involved in what is natural language processing what is natural language understanding and having a computer understand in human terms. And that was the beginning of applying AI. At that time, we were not using the term AI that much. We were using the term cognitive computing usage of computers to solve problems for the common good of people. So that was the objective that IBM wanted to solve. And partnering with hospitals, they identified solving the problem of cancer as their moonshot. And a lot of experiments were done with the hospitals, with the manufacturing companies where predictive models were built, and so on and so forth. So, of course, they were successes and they were failures because all of that depended on data and how data is used to train those models. And the accuracy of those models is very important, especially in medical systems. So that said AI has is, is not new at all. Again, I'll take you back another 50 years now, the term when AI came about, you know, it's gone through its own cycle of spring and winter. We seem to be going through a heavy resurgence of you know, interest in AI today thanks to open AI and all the generative AI hoopla. But this is good because the ecosystem that we are creating is, is very ne very much needed for taking this field forward. How is that going to change the work wave, and how do we serve this digital tide? We all know that COVID brought in accelerated digital transformation and everybody just jumped on to either remote work or you know, learning to live with digital means. You know, the conferences that we use to go to in person now, they're all remote mostly enabled through these virtual technologies. And then there are a lot, many other applications of this technology and ancillary technologies that are going to change the way we go to work. Earlier, we used to have a nine-to-five kind of mindset when we are going to work. But again, today, our life and work are so intertwined through the means of these digital technologies, through the means of these emerging technologies enabled by AI that I'm, I'm very excited to be alive at this point of time.

Tullio Siragusa (07:21):

Yeah. So let's, so let's, let's try to dig in a little bit, but first, maybe go back, right? We're talking about future work and how AI impacts how we work today. When I go back to, for example, the industrial revolution, it took a long time to adopt it beyond farming, right? You know, for 400 years there were inventions made, predominantly used for farming. Because we came, we were in the agricultural age, right? So, it almost took about 400 years before people could imagine other things that could be done with the industrial revolution, like machinery, manufacturing cars, etcetera. And the work schedule was different. People work seven days a week, then six days a week, then we went to five days a week. But now with the knowledge error, which we're kind of moving more into another version of that too, we're still kind of operating under the old mindset. So what are you suggesting in terms of the future work with AI? What should that look like? Is it nine to five? Is it five days a week? Or is it something that could evolve into completely a different approach? Any use cases of how that's being applied today? Just curious to see what your thoughts are on that

Piyush Malik (08:43):

Tullio. Very good question here. And if you see how we have evolved out, we are not nine-to-five creatures anymore. Our work life and our personal life all seem to be intertwined. And I've been saying this for quite some time, that we need to be talking about work-life integration, not work-life separation. That said, accelerated by these digital technologies and AI technologies. Think you know, if humans had resisted you know, those, those kinds of machines that were printing books yes, there were elites who were protesting at that time. Then there were some folks who may have said, well, we don't need automobiles on the road. There are enough horses, or, you know that we need a faster horse. No, we needed to have a shift in our mindset, and that's exactly what we are going to be going through right now. People have been afraid of computers, and they were the famous saying that, Hey, maybe the world just needs four computers. And remember that you know a famous company, a CEO of a famous company, which no longer exists anymore, said that, and now people have been saying AI will take our jobs. Yes, movies have been projecting Terminator-like scenarios that AI, and of course, there are famous tech leaders also have been warning of the dangerous signs of AI. Any technology without guardrails is going to cause upheaval, going to cause our social and work lives to be disrupted. So, what we need to do is to incorporate AI to adapt to it and make technology like artificial intelligence and, part of our life. So, I call that assistive intelligence rather than artificial intelligence. And what it would do is just take the example of OpenAI and Bard. These are tools that are very popular now in the last six months alone since introduction, you know, more than a hundred million users every day. And what do they do? They are able to make our life easier, whether it is to write emails, whether it is to produce images. So, the jobs of folks who, who were just copywriters or just artists that's going to change. AI is going to create music on its own. And we've seen those examples. The challenge there is that all these models, AI models have used data all along, which was created by humans, and they've been trained on it. So the challenge is it could be copyrighted data that was used. And so if something is being generated by ai, would it be patent worthy? Would it be something that could somebody could be granted copyright on? Would there, how would the royalties be paid on it to the people who had originally created that data that was used for training ethics biases might creep in as well because who knows the computer systems. Of course, in the past, there was less representation of women. There was less presentation of people of color. And how that is going to be impacting our life is still to be seen. But there are nations who have released their AI policy and the governance around it is something that we've got to be careful about. And I think if we put our heart and mind to do the right thing combined with the policies, combined with the mindset of technologists we can create a world that is a lot better than what was previously.

Tullio Siragusa (13:04):

You bring up a lot of good points that I think are worth considering in terms of how effective some of these generative AI technologies are based on the training modules. You know, were they trained with some bias or, you know, ethic lack of ethics or neutrality in some regards? And I actually tested this recently. I was trying to find a homeopathic version of something and went on to ChatGPT to say his there homeopathic version of this medication. And, what it presented had a lot of bias and I replied back, this got a lot of bias against homeopathic medicine, which has been around for thousands of years, and it apologized for having some bias. And it was interesting that it is dependent on who did the programming. So what are your thoughts? How do we get it to a place where it is equitable, and it is on an equal playing field where it becomes fair and representative of what's the best interest of all people? How do we get there? What are your thoughts?

Piyush Malik (14:21):

Yeah, so I, just mentioned you said that the homeopathic medicine searching gave you wrong answers. You know, there are a lot of folks who have actually said that ChatGPT is hallucinating. It's, it's essentially dependent on what data it has been fed. And if not, I've been doing data science and using AI ML for my clients over the last seven, or eight years extensively with various kinds of industrial systems. And one thing that we have learned is the system is only as good as the data it is provided. And so the data foundations you know, whether it is the quality of data or whether it is the ongoing governance of that data that definitely needs to be instituted as, as a means of keeping these models sane and creating, creating data products which, which will we serve our needs going forward in an equitable and you a balanced manner as opposed to saying that it's hallucinating. I mean, I'll, again, I'll take you back to an experiment that I believe was a Microsoft that has a chatbot called Thai. And it just kept learning the wrong things based on, and it started using foul language while interacting online. And as so much as I had to shut it off within 24 hours of its release and experiments like that will continue to be made. And again, once again, I bring the point of governance and guardrails in place, and the human in the loop has to be there to be able to guide these systems better. And yes, there is a time that at one point these systems will become super intelligent and much more capable than human's capability. But think of the advantage, you know, the ChatGPT software was able to clear the USLE which is the entrance exam for medical doctors. So, think about the system being used to assist doctors in finding that or diagnosing the disease faster and providing a second opinion, and like that, if this system continues to improve you know, it's, it's an assistive technology. And so, so we've got to put our energies towards the positive things and take it forward and not be afraid of it.

Tullio Siragusa (17:10):

Yeah. Interesting. You made an interesting comment about ChatGPT. Some people think it's hallucinating, and I'm like, that's why it's so smart. It's an ayahuasca journey, that's what's actually happening. All right, so, but let's get back a little bit more into the future of work, which is our topic today. You said something interesting about re-imagining how we work, even the idea of nine to five. So, I think a lot of people are more concerned about, oh, we have these tools now you can get more work done, and what ends up happening is you end up having fewer people doing more work where it's supposed to support, supposed to help us maybe have more flexibility in our lives. You end up having less of it because now you're like, we have these tools that can replicate yourself, so you can do twice as much. What are your thoughts on that? I mean, do we need some guardrail, some ethics, or some, even some legislature on how to effectively use these technologies so that it doesn't create an environment where fewer people are having to do more work now because they have AI? What's the, you know, where you think where, how do you think this is going to play out?

Piyush Malik (18:26):

Tullio there is another <INAUDIBLE> to that? If fewer people are needed then, and these machines are going to replace humans, then what will the displaced people do? Would, would they be unemployed? Would they be, you know, sitting as a burden on society and causing law and order problems? So, all of those issues are interrelated, but the good news is in the technological waves of the past as it happened then, and it'll happen now as well. We will create and end up creating more jobs than what is displaced. It's just that we will have to adapt to it. Whatever we are teaching our kids in schools and colleges today will not be relevant five years from now. Yes, the base would need to be there. And so if we need to have our education system in such a manner that we are teaching our kids and the next generation logical thinking, creative thinking, and ability to adapt, ability to you know, be able to solve problems, and that's the inherent ability that will propel them forward. Talking about how we take this a little bit in the direction of what the legislation the lawmakers need to do what do the technologies need to do? So technologists will need to continue advancing this. And I know there have been calls for, from some leaders to have a moratorium on the development of these systems for six months. And I think that's not going to happen because there'll be nation-states who will use this as a competitive advantage, and they wouldn't want to do so. So, all in all you know, I want to say here that just as an example Khan Academy released ChatGPT enabled personalized tutor, which basically calibrates its instructions to the need of each individual student through the personalized avatar that is there. And that's how the future of education is going to be looking like. That is a very positive way of seeing how our future of education would be. And as a result, as an extension, our workers in the workplace could be trained accordingly using AR VR XR technologies. And you may call it metaverse, but I would say it's a combination of all these technologies together where it's an adaptive learning system, which continues to measure the progress and also calibrate the lessons and just in delivers, just in time whatever is needed by that worker to learn to do their jobs better. And so given, given all of that that future definitely looks much brighter to me using the convergence of all these technologies and of course driven by this digital wave and driven by this AI technologies.

Tullio Siragusa (21:54):

You know, as I'm listening, I can't help to think that perhaps one of the best skills that can be developed, that should be developed is how to effectively collaborate and not necessarily with other people only, but symbiotically, even with AI, you know? Because what you're suggesting is that those who know how to collaborate best and be adaptable, not just with people, but with the machines, can leverage this into a way that benefits them versus those who might, you know, maybe struggle with those kinds of collaborations will find themselves a little bit behind. So yeah. What can companies do, to help make that shift, you know, away from the fear and into being more adaptable and collaborative? Have you, are you seeing some movements in that, in, in those areas from some companies who are kind of, kind of, you know being ahead of this and planning ahead to, to create an environment where there is that symbiotic relationship or, or absolutely. Or company way behind? What are your thoughts on this?

Piyush Malik (23:02):

Absolutely. So the forward-thinking companies, especially the tech companies that I deal with in Silicon Valley they've all jumped onto this generative AI bandwagon. I mean, they had been experiment experimenting with AI and ML systems anyways, but now almost all of them have come up with systems that are built on top of generative technologies. You see the news whether it's the collaboration between Microsoft and Open AI, or whether it is Google introducing new generative tools. And as a matter of fact, yesterday also there was news about a company Snowflake acquiring Niva again, a different kind of search engine using generative technologies. So, all of them are either scrambling to acquire partners or built on top of ChatGPT So the API-enabled interface that OpenAI has made available for building applications on top of ChatGPT and similar systems the more than 200 startups that have much roomed in the last three months alone. And the amount of VC money that is going in there, they're building new and new systems. So, so while the tech companies are adopting it much faster, the older companies, and the traditional businesses have also not stayed behind. JPMC announced a ChatGPT enabled system which they will be making available to their end customers for reselling as well. So, all of these folks, whether it is cutting-edge tech companies or whether it is older companies, they are getting onto the AI bandwagon. I'll give you an example of a mining and manufacturing company. You know, and we used to, I mean, this is a real example where I have helped those companies in the last three to five years. How we started working with the early version of generative AI systems. Google had released something called the bird Model again trained on the corpus of data, all the emails that came out of the Enron scandal. So there were a lot of words and they were able to predict, or what is going to be the next word, and so on and so forth. So, through those systems, we were able to use some of those early models and create a predictive maintenance model for predicting when a particular component in a large industrial system would fail and be able to order ahead those parts or do preventive maintenance ahead of time so that we can avoid the costly downtime. So this is a very simple example. Again not cutting edge, ChatGPT, like, but we've been using it. And now you, if you add ChatGPT onto it and ChatGPT like systems and advanced AI systems, it's only going to get better from here. So I'll just give you one example, but then there are tons of clients who are in, in, into, into this. And they're just adopting it like anything. Whether it is quantum computing or whether it is crypto or whether it is cybersecurity, all of them are going to get benefited by the synergistic relationship adopting these newer AI technologies. And that's the future. We are looking for our work.

Tullio Siragusa (26:47):

Piyush, thank you for being with me. We're up on time. It sounds to me that we might need to change the name instead of artificial intelligence. I like the idea that you mentioned of assistive intelligence or adaptable intelligence that might make it a little less scary for folks, who knows, maybe we'll all agree that change that name needs to change a little bit to make it more human-friendly, but it's been.

Piyush Malik (27:14):

The name? But yes, absolutely. We need to, or at least.

Tullio Siragusa (27:18):

How we think about it, should definitely change. So thanks for being with me today. Really appreciate your insights. A lot to be seen as AI begins to reshape how we think about work and how work gets done. We've seen this sort of evolution over the past hundred-plus years. You know, going from the agricultural age to the industrial age to the knowledge, age, and work has changed even how many, how many hours or days we work has changed. Many people are talking about four-day work. So no, that all could be possible with AI. We'll see how it plays out. Ultimately, let's hope it makes our lives better, not worse, worse. So thanks for being with me. We got a new guest coming on next week on Tuesday. We've got let's see. We have Lisa Thee who's the managing director of Data and AI Launch Group. So, we'll be talking about an interesting conversation about the AI-driven future, about trust, safety, and business success. We're continuing on this AI theme. So come join me again next Tuesday at 9:30 AM Pacific. And you can also check out all the upcoming shows and guests on techleadersunplugged.com. Just go on the website, and you'll find upcoming guests and also all these shows get converted into a block. So, if you want to read about it, and get a little more insight about the topic there's a blog for every one of these shows that you can find on techleadersunplugged.com. Thanks for being with me. Have a great weekend, weekend everyone.

Piyush Malik (28:57):

Thank you for having me. Have a wonderful time. Take care.

 

Piyush MalikProfile Photo

Piyush Malik

Chief Digital & Transformation Officer

Piyush Malik is a startup executive, entrepreneur, board advisor, and business transformation practitioner in the domain of emerging technologies. His core expertise has been in transforming data into business value and improving customer experiences by delivering strategic and innovative capabilities that use analytic insights to enable growth and productivity.

As a CDO, Piyush specializes in harnessing the power of data-driven innovations driving the adoption of cloud-first technologies and rapidly accelerating AI/ML and automation journeys in the enterprise. As an organizational transformation agent, he believes in combining the power of people, culture, and technology to generate outsized returns for the stakeholders. He does this by focusing on the customers' unmet needs and collaboratively building on the foundation of immersive experiences.

Previously, as SVP at SpringML, a premier partner to Google and Salesforce, he focused on strategy, digital transformation using data science, IoT, and all things related to advanced analytics in the cloud. Formerly he led the Worldwide Big Data & Analytics Center of Excellence within IBM’s Digital consulting business and was appointed as a member of IBM's Academy of Technology in 2015. Before that, as a Global leader in IBM's Strategy & Analytics consulting practice and as Information Integrity practice leader at PriceWaterhouseCoopers, he had built worldwide teams and scaled his firm's businesses many folds while working with several Fortune 500 organizations across multiple indust… Read More