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Make sustainable products, sell, repeat


“We call it single bottom-line sustainability, where I look at the single bottom line of all those elements, and I start attaching sustainability to it,” Glickman says. “And I start looking at changes of value and then I can build a business case for change.”

As companies set sustainability goals—to be carbon neutral by 2050, for example—they’re tackling complex challenges: regulations change, supply chains are complicated, especially during the current pandemic, and integrating new technologies into legacy systems is almost always a hurdle, technologically and culturally.

Glickman suggests an incremental approach—he calls it micro change, embracing the fact that sustainability isn’t a one-and-done paradigm shift. “These are things that can be done in a six-week period, eight-week period, that have tangible proof of concepts that can be measured, that can be done at different levels.”

Looking at current infrastructure investments, particularly in North America and Europe, as well as the increasing interest of stakeholders, the sustainability bar is expected to rise. “For the next three years you will see a lot of investment. You will see countries or businesses that want to be leading because they see an advantage,” says Glickman. “Then you will see others have to move along in that direction also.”

This episode of Business Lab is produced in partnership with Infosys.

Full transcript

Laurel: From MIT Technology Review, I’m Laurel Ruma, and this is Business Lab. The show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace.

Our topic today is sustainability, but on a global scale, from factories to supply chains to sustainable development goals for all the countries in the world. It’s possible to design for sustainability, get a return on investment, and help fight climate change. Two words for you: inflection point.

My guest is Corey Glickman, who is the vice president and head of the sustainability and design business at Infosys. Corey is an expert in strategic design, digital transformation, customer experience strategy, and the use of visualization applied to the development of innovative products, processes, and services. He’s a member of the World Economic Forum Pioneer Cities Working Group and a Singularity University faculty expert guest lecturer. He was named one of the 100 most influential designers of the decade by the American Institute of Graphic Arts. This episode of Business Lab is produced in partnership with Infosys. Welcome, Corey.

Corey: Well, thank you, Laurel. It’s a pleasure to be here.

Laurel: So, how does Infosys help customers with design and sustainability? Is it possible to design for sustainability?

Corey: I think it’s absolutely paramount to link sustainability to design. The idea of the definition of design is, how can you take the components that you might have available or components that you can create, and organize those into the optimal system of achieving the result that you’d like to see?

So, when we start to look at the complexity of the systems which make up sustainability, whether that’s the environment, the social, the governance, having a multi-system approach and being able to design those components and how they interlink with each other goes hand in hand in our approach.

Laurel: Everything is obviously becoming more and more complex. A car is a computer with four wheels. How does that forward-thinking play into every step of what a company might mean when it says we want to be sustainable?

Corey: Yeah, I think the car is a great example. I think another way to think about it is to think of a building. So, anywhere we spend time, we expect certain experiences to take place. We expect certain levels of performance. We expect it to get us to a location or for it to create an environment in which we’re at. When we start thinking about these complex systems, though, how do you do everything from the creation of that element or component to the ongoing operation and maintenance? And then ultimately, what happens after it starts to not have the levels of performance that you would expect either from expectations of comfort or experience, or even the performance of safety coming across here.

So, when we look at these systems around sustainability, we are no longer just creating or taking objects and saying, we’re going to use them until they’re no longer satisfying our certain needs. We are now saying, if we’re going to design a product or use a product, we’re thinking from the very first moment what happens afterwards. “How do I source those materials? How does it function efficiently? And then ultimately, can it be reused? Can it be recycled?”

And ultimately, for these complex systems, there are many components. Think of it as a supply chain. No car is built by one company. I think most cars have up to 17,000 different components of suppliers that come from somewhere to go across there. So, being able to organize and to be able to produce something, cars are amazing things. I would actually say that they probably could be the most complex thing that we actually create as humankind because you’re talking about materials that can be collected and gathered, that can be converted from raw materials to a finished product in some of the most advanced plants in 45 minutes.

They have 10,000 computers inside of them. They perform well for 10 to 15 years. They do what they’re supposed to do. They may get to a certain price point, and they provide so much value to the end user for what we need. What we’re questioning now, though, is how long should they last? Or should they be more energy efficient? Should they have less emissions coming across there? What does it mean to have these to be digital extensions of ourselves? So, it is a really interesting problem to solve right now.

Laurel: How has the covid-19 pandemic affected sustainability efforts?

Corey: Well, I think it’s been really twofold. I think most of us have recognized that we saw with covid how it could devastate a supply chain or impact a workforce and just disrupt what we were basically taking for granted of what normal meant. And as companies and organizations had to adjust for that, we changed what normal meant again. So, maybe we didn’t go to the workplace as much in most cases. We didn’t start attending certain public events. We had to adjust how to still be productive. And there were many things already in place, like for instance, e-commerce was there, so therefore you could order food, or you could order goods and still have them delivered to your house.

There were technologies in place that would allow for safety through camera vision or certain kinds of IoT sensors that would tell us air quality and once again keep health and safety through here. But what it did show was that we could be extremely disrupted, that our technologies could adjust, but there were issues around how quickly could we get to those solutions, and could it be impacted globally? When we start thinking about how this would work as I think as a preview for sustainability that we’re going to see and are seeing the same disruptions with sustainability that we saw with covid; however, these are going to be much longer lasting. It won’t be as simple as coming with the right vaccine or the right supply chain.

I think the second element that I’ve really been looking at with the idea of and the advent of covid is, it is I believe a future cast of additional things that we’re going to see, and it is directly linked to sustainability. As we deforest, as we start influencing our biodiversity that’s happening, there are going to be more and more situations where diseases are going to jump from other species to humans because we’re deforesting. We are changing their habitats and they’re becoming closer to our urban centers.

The other thing that happens is, as the Earth gets warmer and moister, that even breeds more disease opportunities through here. So, covid kind of has both sides of it. I know not so many have talked about this second component, but I think that a new wave of health challenges are going to come along with this whole aspect, and covid is one example of them.

Laurel: And that disruption of business applies to, as we’ve seen, forest fires around the world, not just pandemics.

Corey: Oh, absolutely. And it’s interesting that you mentioned forest fires. So, I think we can all make that link to say, “Well, weather’s changing, climate’s changing, and there’s forest fires.” Many companies’ sustainability programs that have corporate social responsibility (CSR) components are often tied to reforestation or afforestation through here. And their economics of sustainability is tied to those programs. So, what happens when those forests are starting to burn? Now your environment, social, and governance (ESG) investments or how you’re doing your carbon credits are also being impacted across there.

So, some very large companies have tried to say that they are closer to carbon neutrality or have made these big inroads, but they’re tied to forests. But if these forests start to go away, then that whole dynamic starts to change for their company and their economies also.

Laurel: And CSR is commitment to social responsibility?

Corey: Exactly.

Laurel: Excellent. That leads us to, what are some of those practical measures that enterprises can implement when they’re trying to create a sustainable framework?

Corey: So, a really important concept for me is this idea of practical frameworks and practical actions. I’m fortunate enough that I work within an organization, at Infosys, where we’ve been carbon neutral now for two years. It’s a fairly large organization, about $13 billion in revenue, 270,000 people globally in 53 countries. And we are more digitally inclined than we are, say, materialistic because we provide technology services, digital transformation components, but we still have 50 million square feet of buildings. We have a lot of transportation, and then we have our whole supply chain coming across there.

And we were able to achieve our carbon neutrality through a commitment over a 10-year period that said we were going to take 10% of our carbon out year over year. And that was our 10th anniversary two years ago, and we pretty much were able to stay on schedule. And I think what’s interesting about it being practical is this: we said we could do this through technology. We could do this through understanding our governance and change, and we could through cultural adoption and communication coming across here and setting our targets.

When it gets to the technical aspects of it, it really came down to two technical components that we really strived for, and then third was a cultural one. So, the technical one was saying, “What are all the assets that we have and how can we optimize those assets to be as efficient as possible, to be produced as low carbon as possible?” Whether that’s buildings or IoT devices or robots or things that we use within our world here.

The second aspect was what could we do with energy transition and transmission, starting to create large solar fields where the environment would allow us to do this? A good example would be in the Bangalore region, where we have one of our large tech cities, we’ve created a 60 megawatt field that is all solar panels. And we also designed and created solar-powered robots that do the upkeep and maintenance of these panels. And then we’ve installed artificial intelligence inside of these robots. So, they can basically predict the weather, or they could recognize if a panel in that system is not working properly. Is it an anomaly, or is there something seriously wrong in those systems? And we do these through control centers.

The third aspect, though, is really the idea of, what could we do around the local communities? When we achieved our carbon neutrality, we did not purchase carbon credits. Not that we think that’s a bad thing because that part of the economy is extremely important for institutions and companies to be able to fund these programs. But we felt that we could create jobs, we could create new environmental and economic impacts into areas where we could implement solutions. So, we have impacted hundreds of thousands of families in those local communities, and we have several programs like that.

So, those were really important. And to kind of sum up is this: if we could do this in, say, 10 years, and knowing the technologies that we knew starting 10 years ago and as they evolved, as we look and work with companies and we say, “We can take, starting out with your data and understanding data and understanding both your physical and your digital technology components, we could probably solve 50% of what your goals are in a five to seven-year period based off our own experience of what we’ve actually have done for ourselves and have done for many of our partners and clients across there.”

So, there are frameworks of existing technologies today that, when you couple with the fact that the need for sustainability will exist for at least the next 50 years from a business case perspective, therefore we know those investments and ROIs will come to return beyond just the social and the health aspects. And third, that the culture is ready now for this. It’s just the fact that everybody’s kind of at a different stage—are they ready for it? Are they willing to make that investment? How would they measure those values? So, applying practical approaches, known technologies, proof of ROI, there are many, many frameworks out there that can have at least 50% impact on your goals.

Laurel: That’s amazing. So, you mentioned a cultural shift as a company. Sometimes people are the hardest part of a shift, and technology can be easy. What advice do you offer to a company that’s trying to culturally change to be a sustainable or sustainability-first type company?

Corey: First of all, you said it absolutely right that cultural change is extremely complex. And most companies have gone through programs of cultural change, whether it was through digital transformation or even covid policies. Everything is, how do I change culture and where does that reside across there? What we have seen work best is concepts where we look at micro change.

So, if you think of the picture in your mind, the traditional way that change management is done in large organizations, usually it’s this S-curve model, where you start at the bottom of the S and the tip, and you start to make a change and then you have a lift and then it kind of loops back down, and then you hook another S to it. It’s almost like that barrel of monkeys trick. You’re trying to hook things together and keep on going up the chain here.

When you look at micro changes, these are things that can be done in a six-week period, eight-week period, that have tangible proof of concepts that can be measured, that can be done at different levels. And these would be different formulas depending whether you are the governance factor or if you are at a project factor level, or if you’re at an HR factor. But this idea of lining up micro changes that are provable and measurable we have found to be extremely valuable across there.

Of course, the standards around communication, continuous learning is extremely important through here, but we find that where the advantage is with sustainability, there’s very few people, if anybody on the planet, that’ll say sustainability is not a good thing. So, at least you have that part of the argument won. You usually have to question, can I afford to do this—or can I afford not to do this? is also so a question. And it really becomes a model that goes back to what we call value realization.

So, ultimately for businesses to make that change, for that top leadership to really make the investment, they’re going to say, “When is my return on my investment? What do I gain from this? What do I lose from this?” And there’s this whole idea of exchanging value in the business, exchanging value and how you do things. We call it single bottom-line sustainability, where I look at the single bottom line of all those elements, and I start attaching sustainability to it. And I start looking at changes of value and then I can build a business case for change. And then it’s a matter of rolling that out and getting the buy-in across there. It’s a really fascinating science.

The last mental model that we’ve seen that I’ll kind of put in viewers or listeners’ heads is this: think of it like an hourglass. So, at the top of that hourglass, you have senior leadership that gets this. They understand this is the future. This is the economy. It’s also the now. It has to take place. And we’re finding that leadership is extremely competent, unlike, let’s say, that past waves that people weren’t very competent, but there was often this technology learning curve to say, “Well, what will this technology do for me? How will this give me good business, etc.? How will my partnerships work?”

We’re finding that this generation of individuals and leaders in sustainability in these organizations are not just very technology savvy, they’re also very savvy in building companies and making change happen, so we know that is very good. And then at the bottom of the hourglass there are a lot of pockets of excellence that can enable things to take place, and that is very good. But in the center that kind into this pinch point like in the center of an hourglass that says, “What’s holding me up? Why can’t I make that whole organization go here?” And that could be through partnerships. It could be through governance rules. There’s a bunch of reasons of why that’s tight.

And I think that there is not enough focus to how to unlock that right now. Many companies, many partners, many governments will talk about, “We need to do this. Here’s the benefits for here. Here’s even enabling technologies and so forth.” But how do you convince that population to buy into it, and how do you get that to become something that becomes a continuous new norm for us? That I think is a fascinating science and it’s a big part of our practice.

Laurel: I like that idea of incremental change. You have to keep trying it in various ways, and it’s not just all one and done in one shift. So, there are obviously obstacles that enterprises need to expect when integrating sustainable practices. What kind of approach do enterprises need to think about when they have legacy systems?

Corey: So, that’s a really good question because I think it depends on certainly what type of company or institution that you’re talking about. So, if you are a large materialistic company that produces lots of physical things, has lots of carbon in it and those companies are absolutely vital for how we live and exist. They have a much bigger issue to solve because they’re always going to be producing carbon. They need tons of energy. They need the ability of raw materials and they’re able to have to work down a huge supply chain through here. But if we don’t have these companies, we’re not going to have much in our lives to exist to be quite honest.

And then there are companies that are more digital. So, they have a different set of problems to solve. Maybe it’s about how much cloud services they’re using or the kinds of interactions and how they produce code and provide services. And then there are other types of companies, which are fully in the mode of, it’s all about financial. And how do things get funded and how do they enable these supply chains for the, let’s call it a carbon economy to work.

So, those obstacles in each of those instances: if I’m this large material company, I have to make decisions of where do I source my materials? How do I produce those materials? How do I start thinking about circular economics so I can get better reuse, longevity, the right kind of scheduling? But these products must enter the world’s marketplace or we’re not going to have much society to be quite honest. So, their obstacles are always decisions about cost point, trading off the quality of building something that is going to work in exchange for being more responsible for less waste and therefore production, and then how that whole supply can work.

So, they have some big obstacles. They might be able to solve parts for themselves, but because they’re so dependent on their suppliers, how do they get their suppliers to line up there? And I think part of that answer has to do with data. Kind of building off the idea of data, if you are a financial company what you want to basically do is say, “Can I get enough data to understand what is the carbon situation for the companies that I choose to finance or lend money to or what private equity might want to go after?”

So, being able to capture data, measure data, start to analyze and predict where those investments should go in place along with other aspects to say, “My portfolio should look like in the following way and I should only be funding certain types of companies and give them better credit rates.” Those are decisions to make, too, because if there’s money to be made, say, outside that box, those are decisions to also to be determined. So, there’s some obstacles there.

If I’m a digital company, the obstacles are going to be, we are moving more and more towards digital. With the new Meta idea coming through, that means even more computer power and more folks and participants using more computing power across the way, and maybe not relating as much to the physical space outside of there. There’s obstacles, because companies are going to see that there is great opportunity in delivering digital transformation and providing server technologies and cloud. And that’s just going to grow and expand.

And edge and 5G and all of these areas, they will look at sustainability for the technology, but it’s going to be more rampant to rush to say, “How quickly can I get into that marketplace and become a leader in these new digital areas?”

Laurel: You touched on this earlier, but there is also the need to balance business requirements like the return on investment. So, what does the return on investment look like for implementing sustainable approaches and technologies?

Corey: I’ll give you a couple of examples here because there’ll be some variations on how to look at it. So, one area to think about is the built environment. So, that would be the buildings and by extension our cities. And I bring that up for two reasons. So, buildings are either brand new or they are going to be retrofits. And why buildings are so important: 90% of the population lives in cities. The built environment actually accounts for 40% of all the emissions and climate change issues. So, that’s everything from the planning to the actual creation of the structures, and then the ongoing operations through there.

So, we’ve got to solve for this because if we don’t solve for this, it’s a big issue. Because we can do everything else, but if you’re missing 40% of the solution, 60% is not going to get us there. So, when we come to buildings, if you’re going to retrofit a building or if you’re going to create a new building, generally the return on investment for a more sustainable component or buildings generally somewhere between one to three years that you can actually start seeing that return on investment in a pretty tangible way. So, that is something that we always advocate as you optimize and come across there.

I think from an investment perspective if we’re looking at the financial markets with return on investment, there’s a lot of mixed messages that are happening there. So, everything from, “Well, what does cryptocurrency combined with blockchain mean if we’re going to do sourcing down a supply chain?” It’s extremely volatile right now. The idea of ESG investing is continuing to grow. There’s certain risks that are involved, but we do know that’s the future. And we can see companies that do this certainly outperform and investors who actually go in this direction, their portfolios do better, too.

Where it becomes a bit of a risk though is because it’s now so closely associated, and continues to be, with cryptocurrency, and the market’s not fully understanding that yet, there is some risk involved across there. But you could see pretty large returns on investment through here.

And then I think the real question comes down to, if you’re not a mega company or tier one, or if you’re not one of these large banks, but you’re a tier two or a tier three, which are absolutely vital, because most of the businesses and companies that make up our supply teams are that level, it’s harder for them to invest and it’s harder for them to get the right technologies. It’s harder for them to be able to put people resources or data resources against there. And they’re the ones that are at risk—equivalent to very wealthy countries versus maybe countries that will not have as much wealth in order to make the adjustment. And kind of going back to the covid idea, if you don’t solve it for all and you leave pockets where there’s holes in your wall, then variants are going to keep on coming up, that are going to continuously challenge the overall supply chain model. And once again, we’re not going to get there.

So, it is really, really interesting. I don’t know if you’ve noticed it, but I’ve seen a behavior pattern where there’ll be governments, which I fully believe have the best intentions for their own people and societies, that will set up regulations and they will go ahead and do what they feel is best to do for those countries. And they’ll set these deadlines and they’ll make agreements. And then you’ll find pockets of whether it’s cities or companies maybe within that government says, “No, I need to go faster, or I can be more innovative than what the government is saying.”

And then there’s big opportunities for return on investment there, by going faster or going after a technology, bending the rules a little bit. There are ways for this capitalistic kind of approach to invite innovation.

Laurel: Speaking of that kind of innovation and perhaps going faster than regulatory rules allow, what about Industry 4.0? How is the change and evolution of technology and manufacturing affecting sustainability efforts?

Corey: Yeah, I think there’s a huge match for Industry 4.0 as we talk about sustainability. So, if we think about, it’s really a more conscientious use of natural resources. How do we have less waste? Can we take those lean ideas and processes and put those into the life cycles of machines and equipment in longer systems? There’s always this idea that says, “Do I build a product that lasts longer and therefore doesn’t need to be replaced as often?” And what does that benefit over, say, a product that might have a shorter lifespan, but perhaps has a higher value as a reuse piece.

So, a good example would be like the battery economy. So, we all first think of the use of batteries for the future of electric vehicles (EVs) and those kinds of vehicles. And I’d say just on an average, I don’t have the exact statistic, that a good EV car battery is going to last five to seven years and then we’ll start seeing a pretty steady performance drop based off of today’s technologies. So, what do you do with that battery? That battery still has great use in it. And the fact of matter is, it still has 80% of its potency. It’s no longer just the matter of that it can no longer operate that vehicle to that certain level that you expect for performance and safety, but you can re-channel that battery for the use of powering IoT devices or perhaps use within houses for systems within buildings.

So, there’s that opportunity to reuse that. And sometimes you have to think outside the box that what I assumed was in my supply chain. Instead of just saying, “I got to recycle that battery or somehow rebuild it or recharge. What if I shifted over to another cycle into somebody else’s supply chain where it has continued use?” And people are thinking like that. I think Industry 4.0 is going to help recognize those opportunities and help institutions and individuals and inventors and large companies make those decisions better as we produce machines or the objects that we use every day.

Laurel: So, as everything evolves so quickly, what about artificial intelligence? How do you see AI playing a role in sustainability?

Corey: So, I think the biggest benefit to artificial intelligence is obviously not just the speed, but also the ability to combine data in ways that is more advanced than any one human or group of humans could possibly do. And the idea of these complex systems that we’re looking at—so, if we have to start taking a mix of: I need to understand climate. I need to understand a financial cycle. I need to understand a complex supply chain. Or, even if let’s say I take a building as an environment and I’m running building management systems, I’m running security systems, health systems. I’m running civic systems. I could be doing ingress and egress patterns. I could be looking at cybersecurity ransomware.

These are large, complex problems to go through. So, having artificial intelligence to be able to not just understand this, but actually start to predict what are possible outcomes or what are the trade-offs coming across there and being able to isolate anomalies that therefore, maybe a human needs to come in to just look at anomalies versus the overall continuous going forward or the ability to self-heal.

I mean, there’s lots of interesting components, but what I would say, at least what I’m seeing at this point, is what data, what artificial intelligence, does, which is extremely important, is sometimes called thin data. It goes very fast. A lot of decisions are made. Some amazing algorithms are put out there that allow for optimization, but there’s also this need for thick data at where humans have to get involved in order to perhaps make the right decision when it comes to two points across there. I do know that the more that artificial intelligence advances, especially with ideas like quantum computing and other new sciences and edge devices, we’ll continue to see a proliferation of artificial intelligence.

Technology’s never good or bad. The question ultimately is, will society accept it? Will it be used, or how will it be abused, and how will we go forward on this thing? But the genie’s out of the bottle. So, it’s really all of our jobs to protect privacy, but also take advantage of this. I could say without artificial intelligence, we probably, once again, could not have created a covid solution as quick as we could from a vaccine level, as an example.

Laurel: That’s all really amazing when you think of it coming together to actually be able to respond so quickly. And as you said, in these times, any kind of disruption could be cataclysmic, not just for humanity, but for a company itself. So, how do you see the next two to three years playing out for sustainability efforts across enterprises and industries?

Corey: I know what I’d like to see, and then I’ll tell you what I think I’m seeing. So, what we’re seeing is some companies, some countries, some individuals just going faster and saying, “Things need to move in a certain direction to start correcting.” I don’t know if it’s correcting an issue as opposed to saying, what is the future going to be? I think there’s a mind shift that says the generation that exists right now, the older generation, I’m part of that older generation, is saying, “Well, how do I continue living longer or have a job or have the economy so it’s good? I don’t get into a worse situation.”

And then there’s also the generation that’s the future side that says, “You don’t want to be stealing or robbing from that future generation.” What is that future generation going to end up with here, across here? So, I think over the next two or three years, we certainly will see with the investments that are happening, particularly in Europe and in North America on infrastructure, and also the fact that regulations are starting to come into place, and this huge market surge around technology and ESG that for the next three years you will see lots of investment. You will see countries or businesses that want to be leading in this because they see an advantage coming across there.

And that’s a benefit because if some companies or some countries can prove that things can be moved in the right direction and that it will not harm the economy, but only boost it, then you will see others have to move along in that direction also. And hopefully that will lift everything up there. I, once again, look at three specific things, talk about what are the practical things that you can be doing right now based off of technologies that exist. What can we do with our buildings through there? We saw this with covid. How did we make our buildings safe? We were able to convert those building over in what, half a year to two years.

So, technically you could go back to that workplace. You could monitor across there. We could be doing those same things in sustainability through retrofits or through some new technologies based off of existing technologies, and we get that return investment in those three years. So, I think that’s important because that’s also going to help with understanding where population shifts go and how we choose to work and so forth through there.

I think also that the concept of these micro changes and the consumer values of saying, “I will choose to purchase from this company versus another company, or choose this product over another product.” We’re becoming much more conscientious about it. I think one of the challenges that will face the generation that’s entering the workforce right now is twofold. In some ways I would say they’re the most entitled. They have more technology access, more data access than any other generation. And therefore, they can make very strong decisions because they have that at their fingertips, or they know how to go through this.

The question will be as they are looking for whether they want to be doctors or engineers or pet store owners or whatever, how does sustainability work into what they’re doing? And I think they’re all asking this question right now. We do quite a bit of work with different schools and that always comes up with saying, “I was set on this one career. I’m now highly interested in sustainability. Do I get a career in sustainability, or do I get the career in what I’m looking for?”

So, I think that’s really hopeful that the generations are saying, this is just going to be embedded or this is how I’m going to think across there. At the same time, I think that it will be very, very challenging because of the amount of knowledge that is out there, there’s going to be some hard decisions they are going to come across. I’ll give you an example. Let’s take decarbonization. So, we all agree that we should be using energies that are renewable as much as possible to move in the right direction.

Different companies or different countries have different times across here, but where that could happen. Should it happen at the government level that is supplying your energy and therefore they can regulate it? And therefore you’re pretty much guaranteed that if those regulations are in place, decarbonization will take place in those communities into those businesses. Or, do you put it in the hands of the private companies that are using that energy to say, “They’ll take responsibility for decarbonization.” And therefore you might see more innovation take place.

So, therefore you see something like a Tesla come up where it’s saying, “We’ve got new battery technologies and so forth.” And the whole world benefits from this. It’s not just from the technology, but also from the growth of investments and how economies work and just really change how we think about things. But the big question then comes out as saying, “If I start providing access to information around how people use energy and I’m putting in the hands of private companies, what will they do with that information?” Because it’s something we’ve never really done before. That’s always resided at a government level and that’s kind of societal.

So, those are big questions that have to be answered that the more we turn over to private side where we might see a more innovation, we’re also so turning more of our data over to the private side. And those are big questions to be asked. So, I think over the next three years you’re going to see a lot of private companies based off of the ability to be successful in the future economy be very innovative and ask for more control.

And I think you’ll see governments willing to get of parts of that because they know those private companies can move quicker. But at the same time, governments can be very leery about how much of that private information starts leaving their hands and going into hands that maybe they don’t have a clear view on.

Laurel: Excellent. Corey, thank you so much for being with us today on the Business Lab.

Corey: Well, thank you. I love talking about this, and this is just a great conversation to have. But more importantly, it’s the actions. It starts with the micro changes and having these conversations. So, it was my pleasure to be able to join you today.

Laurel: That was Corey Glickman, vice president and head of sustainability and design business at Infosys, whom I spoke with from Cambridge, Massachusetts, the home of MIT and MIT Technology Review, overlooking the Charles River. That’s it for this episode of Business Lab, I’m your host, Laurel Ruma. I’m the director of Insights, the Custom Publishing Division at MIT Technology Review.

We were founded in 1899 at the Massachusetts Institute of Technology. You can find us in print, on the web, and at events each year around the world. For more and about us and the show, please check out our website at technologyreview.com. This show is available wherever you get your podcasts. If you enjoyed this episode, we hope you’ll take a moment to rate and review us. Business Lab is a product of MIT Technology Review. This episode was produced by Collective Next. Thanks for listening.

This podcast episode was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

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Why I became a TechTrekker

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group jumps into the air with snowy mountains in the background


My senior spring in high school, I decided to defer my MIT enrollment by a year. I had always planned to take a gap year, but after receiving the silver tube in the mail and seeing all my college-bound friends plan out their classes and dorm decor, I got cold feet. Every time I mentioned my plans, I was met with questions like “But what about school?” and “MIT is cool with this?”

Yeah. MIT totally is. Postponing your MIT start date is as simple as clicking a checkbox. 

Sofia Pronina (right) was among those who hiked to the Katla Glacier during this year’s TechTrek to Iceland.

COURTESY PHOTO

Now, having finished my first year of classes, I’m really grateful that I stuck with my decision to delay MIT, as I realized that having a full year of unstructured time is a gift. I could let my creative juices run. Pick up hobbies for fun. Do cool things like work at an AI startup and teach myself how to create latte art. My favorite part of the year, however, was backpacking across Europe. I traveled through Austria, Slovakia, Russia, Spain, France, the UK, Greece, Italy, Germany, Poland, Romania, and Hungary. 

Moreover, despite my fear that I’d be losing a valuable year, traveling turned out to be the most productive thing I could have done with my time. I got to explore different cultures, meet new people from all over the world, and gain unique perspectives that I couldn’t have gotten otherwise. My travels throughout Europe allowed me to leave my comfort zone and expand my understanding of the greater human experience. 

“In Iceland there’s less focus on hustle culture, and this relaxed approach to work-life balance ends up fostering creativity. This was a wild revelation to a bunch of MIT students.”

When I became a full-time student last fall, I realized that StartLabs, the premier undergraduate entrepreneurship club on campus, gives MIT undergrads a similar opportunity to expand their horizons and experience new things. I immediately signed up. At StartLabs, we host fireside chats and ideathons throughout the year. But our flagship event is our annual TechTrek over spring break. In previous years, StartLabs has gone on TechTrek trips to Germany, Switzerland, and Israel. On these fully funded trips, StartLabs members have visited and collaborated with industry leaders, incubators, startups, and academic institutions. They take these treks both to connect with the global startup sphere and to build closer relationships within the club itself.

Most important, however, the process of organizing the TechTrek is itself an expedited introduction to entrepreneurship. The trip is entirely planned by StartLabs members; we figure out travel logistics, find sponsors, and then discover ways to optimize our funding. 

two students soaking in a hot spring in Iceland

COURTESY PHOTO

In organizing this year’s trip to Iceland, we had to learn how to delegate roles to all the planners and how to maintain morale when making this trip a reality seemed to be an impossible task. We woke up extra early to take 6 a.m. calls with Icelandic founders and sponsors. We came up with options for different levels of sponsorship, used pattern recognition to deduce the email addresses of hundreds of potential contacts at organizations we wanted to visit, and all got scrappy with utilizing our LinkedIn connections.

And as any good entrepreneur must, we had to learn how to be lean and maximize our resources. To stretch our food budget, we planned all our incubator and company visits around lunchtime in hopes of getting fed, played human Tetris as we fit 16 people into a six-person Airbnb, and emailed grocery stores to get their nearly expired foods for a discount. We even made a deal with the local bus company to give us free tickets in exchange for a story post on our Instagram account. 

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The Download: spying keyboard software, and why boring AI is best

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🧠


This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

How ubiquitous keyboard software puts hundreds of millions of Chinese users at risk

For millions of Chinese people, the first software they download onto devices is always the same: a keyboard app. Yet few of them are aware that it may make everything they type vulnerable to spying eyes. 

QWERTY keyboards are inefficient as many Chinese characters share the same latinized spelling. As a result, many switch to smart, localized keyboard apps to save time and frustration. Today, over 800 million Chinese people use third-party keyboard apps on their PCs, laptops, and mobile phones. 

But a recent report by the Citizen Lab, a University of Toronto–affiliated research group, revealed that Sogou, one of the most popular Chinese keyboard apps, had a massive security loophole. Read the full story. 

—Zeyi Yang

Why we should all be rooting for boring AI

Earlier this month, the US Department of Defense announced it is setting up a Generative AI Task Force, aimed at “analyzing and integrating” AI tools such as large language models across the department. It hopes they could improve intelligence and operational planning. 

But those might not be the right use cases, writes our senior AI reporter Melissa Heikkila. Generative AI tools, such as language models, are glitchy and unpredictable, and they make things up. They also have massive security vulnerabilities, privacy problems, and deeply ingrained biases. 

Applying these technologies in high-stakes settings could lead to deadly accidents where it’s unclear who or what should be held responsible, or even why the problem occurred. The DoD’s best bet is to apply generative AI to more mundane things like Excel, email, or word processing. Read the full story. 

This story is from The Algorithm, Melissa’s weekly newsletter giving you the inside track on all things AI. Sign up to receive it in your inbox every Monday.

The ice cores that will let us look 1.5 million years into the past

To better understand the role atmospheric carbon dioxide plays in Earth’s climate cycles, scientists have long turned to ice cores drilled in Antarctica, where snow layers accumulate and compact over hundreds of thousands of years, trapping samples of ancient air in a lattice of bubbles that serve as tiny time capsules. 

By analyzing those cores, scientists can connect greenhouse-gas concentrations with temperatures going back 800,000 years. Now, a new European-led initiative hopes to eventually retrieve the oldest core yet, dating back 1.5 million years. But that impressive feat is still only the first step. Once they’ve done that, they’ll have to figure out how they’re going to extract the air from the ice. Read the full story.

—Christian Elliott

This story is from the latest edition of our print magazine, set to go live tomorrow. Subscribe today for as low as $8/month to ensure you receive full access to the new Ethics issue and in-depth stories on experimental drugs, AI assisted warfare, microfinance, and more.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 How AI got dragged into the culture wars
Fears about ‘woke’ AI fundamentally misunderstand how it works. Yet they’re gaining traction. (The Guardian
+ Why it’s impossible to build an unbiased AI language model. (MIT Technology Review)
 
2 Researchers are racing to understand a new coronavirus variant 
It’s unlikely to be cause for concern, but it shows this virus still has plenty of tricks up its sleeve. (Nature)
Covid hasn’t entirely gone away—here’s where we stand. (MIT Technology Review)
+ Why we can’t afford to stop monitoring it. (Ars Technica)
 
3 How Hilary became such a monster storm
Much of it is down to unusually hot sea surface temperatures. (Wired $)
+ The era of simultaneous climate disasters is here to stay. (Axios)
People are donning cooling vests so they can work through the heat. (Wired $)
 
4 Brain privacy is set to become important 
Scientists are getting better at decoding our brain data. It’s surely only a matter of time before others want a peek. (The Atlantic $)
How your brain data could be used against you. (MIT Technology Review)
 
5 How Nvidia built such a big competitive advantage in AI chips
Today it accounts for 70% of all AI chip sales—and an even greater share for training generative models. (NYT $)
The chips it’s selling to China are less effective due to US export controls. (Ars Technica)
+ These simple design rules could turn the chip industry on its head. (MIT Technology Review)
 
6 Inside the complex world of dissociative identity disorder on TikTok 
Reducing stigma is great, but doctors fear people are self-diagnosing or even imitating the disorder. (The Verge)
 
7 What TikTok might have to give up to keep operating in the US
This shows just how hollow the authorities’ purported data-collection concerns really are. (Forbes)
 
8 Soldiers in Ukraine are playing World of Tanks on their phones
It’s eerily similar to the war they are themselves fighting, but they say it helps them to dissociate from the horror. (NYT $)
 
9 Conspiracy theorists are sharing mad ideas on what causes wildfires
But it’s all just a convoluted way to try to avoid having to tackle climate change. (Slate $)
 
10 Christie’s accidentally leaked the location of tons of valuable art 🖼📍
Seemingly thanks to the metadata that often automatically attaches to smartphone photos. (WP $)

Quote of the day

“Is it going to take people dying for something to move forward?”

—An anonymous air traffic controller warns that staffing shortages in their industry, plus other factors, are starting to threaten passenger safety, the New York Times reports.

The big story

Inside effective altruism, where the far future counts a lot more than the present

" "

VICTOR KERLOW

October 2022

Since its birth in the late 2000s, effective altruism has aimed to answer the question “How can those with means have the most impact on the world in a quantifiable way?”—and supplied methods for calculating the answer.

It’s no surprise that effective altruisms’ ideas have long faced criticism for reflecting white Western saviorism, alongside an avoidance of structural problems in favor of abstract math. And as believers pour even greater amounts of money into the movement’s increasingly sci-fi ideals, such charges are only intensifying. Read the full story.

—Rebecca Ackermann

We can still have nice things

A place for comfort, fun and distraction in these weird times. (Got any ideas? Drop me a line or tweet ’em at me.)

+ Watch Andrew Scott’s electrifying reading of the 1965 commencement address ‘Choose One of Five’ by Edith Sampson.
+ Here’s how Metallica makes sure its live performances ROCK. ($)
+ Cannot deal with this utterly ludicrous wooden vehicle
+ Learn about a weird and wonderful new instrument called a harpejji.



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Why we should all be rooting for boring AI

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Why we should all be rooting for boring AI


This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

I’m back from a wholesome week off picking blueberries in a forest. So this story we published last week about the messy ethics of AI in warfare is just the antidote, bringing my blood pressure right back up again. 

Arthur Holland Michel does a great job looking at the complicated and nuanced ethical questions around warfare and the military’s increasing use of artificial-intelligence tools. There are myriad ways AI could fail catastrophically or be abused in conflict situations, and there don’t seem to be any real rules constraining it yet. Holland Michel’s story illustrates how little there is to hold people accountable when things go wrong.  

Last year I wrote about how the war in Ukraine kick-started a new boom in business for defense AI startups. The latest hype cycle has only added to that, as companies—and now the military too—race to embed generative AI in products and services. 

Earlier this month, the US Department of Defense announced it is setting up a Generative AI Task Force, aimed at “analyzing and integrating” AI tools such as large language models across the department. 

The department sees tons of potential to “improve intelligence, operational planning, and administrative and business processes.” 

But Holland Michel’s story highlights why the first two use cases might be a bad idea. Generative AI tools, such as language models, are glitchy and unpredictable, and they make things up. They also have massive security vulnerabilities, privacy problems, and deeply ingrained biases.  

Applying these technologies in high-stakes settings could lead to deadly accidents where it’s unclear who or what should be held responsible, or even why the problem occurred. Everyone agrees that humans should make the final call, but that is made harder by technology that acts unpredictably, especially in fast-moving conflict situations. 

Some worry that the people lowest on the hierarchy will pay the highest price when things go wrong: “In the event of an accident—regardless of whether the human was wrong, the computer was wrong, or they were wrong together—the person who made the ‘decision’ will absorb the blame and protect everyone else along the chain of command from the full impact of accountability,” Holland Michel writes. 

The only ones who seem likely to face no consequences when AI fails in war are the companies supplying the technology.

It helps companies when the rules the US has set to govern AI in warfare are mere recommendations, not laws. That makes it really hard to hold anyone accountable. Even the AI Act, the EU’s sweeping upcoming regulation for high-risk AI systems, exempts military uses, which arguably are the highest-risk applications of them all. 

While everyone is looking for exciting new uses for generative AI, I personally can’t wait for it to become boring. 

Amid early signs that people are starting to lose interest in the technology, companies might find that these sorts of tools are better suited for mundane, low-risk applications than solving humanity’s biggest problems.

Applying AI in, for example, productivity software such as Excel, email, or word processing might not be the sexiest idea, but compared to warfare it’s a relatively low-stakes application, and simple enough to have the potential to actually work as advertised. It could help us do the tedious bits of our jobs faster and better.

Boring AI is unlikely to break as easily and, most important, won’t kill anyone. Hopefully, soon we’ll forget we’re interacting with AI at all. (It wasn’t that long ago when machine translation was an exciting new thing in AI. Now most people don’t even think about its role in powering Google Translate.) 

That’s why I’m more confident that organizations like the DoD will find success applying generative AI in administrative and business processes. 

Boring AI is not morally complex. It’s not magic. But it works. 

Deeper Learning

AI isn’t great at decoding human emotions. So why are regulators targeting the tech?

Amid all the chatter about ChatGPT, artificial general intelligence, and the prospect of robots taking people’s jobs, regulators in the EU and the US have been ramping up warnings against AI and emotion recognition. Emotion recognition is the attempt to identify a person’s feelings or state of mind using AI analysis of video, facial images, or audio recordings. 

But why is this a top concern? Western regulators are particularly concerned about China’s use of the technology, and its potential to enable social control. And there’s also evidence that it simply does not work properly. Tate Ryan-Mosley dissected the thorny questions around the technology in last week’s edition of The Technocrat, our weekly newsletter on tech policy.

Bits and Bytes

Meta is preparing to launch free code-generating software
A version of its new LLaMA 2 language model that is able to generate programming code will pose a stiff challenge to similar proprietary code-generating programs from rivals such as OpenAI, Microsoft, and Google. The open-source program is called Code Llama, and its launch is imminent, according to The Information. (The Information

OpenAI is testing GPT-4 for content moderation
Using the language model to moderate online content could really help alleviate the mental toll content moderation takes on humans. OpenAI says it’s seen some promising first results, although the tech does not outperform highly trained humans. A lot of big, open questions remain, such as whether the tool can be attuned to different cultures and pick up context and nuance. (OpenAI)

Google is working on an AI assistant that offers life advice
The generative AI tools could function as a life coach, offering up ideas, planning instructions, and tutoring tips. (The New York Times)

Two tech luminaries have quit their jobs to build AI systems inspired by bees
Sakana, a new AI research lab, draws inspiration from the animal kingdom. Founded by two prominent industry researchers and former Googlers, the company plans to make multiple smaller AI models that work together, the idea being that a “swarm” of programs could be as powerful as a single large AI model. (Bloomberg)

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