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The idea of artificial intelligence may strike fear in the hearts of some business leaders, but there is no need to panic. In their new book, Human + Machine: Reimagining Work in the Age of AI, Paul Daugherty and James Wilson make a compelling case for pairing this particular technology with human capital. Daugherty, who is chief technology and innovation officer for Accenture, and Wilson, who is managing director of information technology and business research at Accenture Research, joined the Knowledge@Wharton show on Wharton Business Radio, SiriusXM channel 111, to talk more about the topic.
An edited transcript of the conversation follows.
Knowledge@Wharton: What inspired the book, and specifically the title?
Paul Daugherty: It started two years ago when Jim and I were working a lot of research around artificial intelligence. We believe that artificial intelligence has immense potential for us to improve the way that people both work and live. The issue that Jim and I saw is that, in contrast to the opportunity that we see today, a lot of the dialogue is negative. It’s about human versus machine. It’s the 50th anniversary of the movie 2001: A Space Odyssey, where we had the HAL 9000 famously say, “I can’t do that, Dave.” There’s a narrative about the machine against the human, and it creates this dynamic that the machines are against us.
We really believe that artificial intelligence is a new technology that can dramatically improve the way that we live and work, and give us better tools to be more productive and more effective. We wrote “Human + Machine” to emphasize that it’s about us being equipped with better tools to do things more effectively. We think that has tremendous potential for business.
James Wilson: We find in our research that companies that focus on human and machine collaboration create outcomes that are two to more than six times better than those that focus on machine or human alone. For instance, BMW has found that robot/human teams were about 85% more productive than the old assembly line process, where you had industrial robots over on one side of the factory and people working on an old automated assembly line. When they got rid of that set up and started bringing people and collaborative robots to work together, they really started to see those big productivity improvements that just weren’t possible through the old way of thinking about automation.
“There’s a narrative about the machine against the human, and it creates this dynamic that the machines are against us.”— Paul Daugherty
Knowledge@Wharton: How does Accenture view AI and its applications?
Daugherty: We see tremendous potential for AI within our business and are investing greatly in developing our business very quickly. We help companies deploy technology and new solutions to run their business more effectively, and we have never seen a part of our business grow as fast as what we’re seeing with artificial intelligence in terms of potential in the real work we’re doing to help clients with AI. Even in our own business, it is transforming the way we do a lot of our work. We use AI in the way that we build systems and solutions for our clients, and we are deploying AI capability to recruit people more effectively and manage our people more effectively.
One of the things that we talk about in the book is this idea of responsible AI, the ethics and new questions we need to answer with AI. We have developed COBE, which stands for Code of Business Ethics, and it is an internal AI-enabled chat bot to help our people better understand some of the ethical issues and questions that come up in business generally but also with artificial intelligence.
Knowledge@Wharton: Even with the growth of AI within your company, the communication element with employees is vital?
Daugherty: A lot of people are daunted by the term artificial intelligence. What does it really mean? The term sometimes scares us because it sounds like we are changing the way that people think. In contrast, we believe this is about humans plus machine and technology and giving us better capability. We use the term superpower because it gives us superpowers with better tools to do things more effectively.
The real important thing is training people to use this technology more effectively. We think it is imperative for business leaders to figure out and put in place new learning platforms and training capabilities so that people are ready for this. Because if the people aren’t ready for AI, I think we will have some issues in business and in some communities. The imperative that we all face is not the lack of jobs, which is sometimes the focus, or the machines taking the jobs, which we don’t really think is the reality, but it’s preparing people for the new jobs that are coming.
Knowledge@Wharton: But every company is looking for efficiency, correct? Artificial intelligence can take us to that next level of efficiency, whether it be within the office or outside on sales or in HR.
Wilson: You can keep pushing for more and more efficiency with artificial intelligence, but what we’re finding really is that we’re moving from an age of efficiency focus and automation to an age of imagination. As we began to look at leading companies, we started to see that about 9% of companies that were really getting the most potential out of artificial intelligence were reimagining old processes rather than just making them more efficient.
“We’re moving from an age of efficiency focus and automation to an age of imagination.” –James Wilson
For instance, General Electric is using intelligent agents to empower its maintenance workers to make multimillion-dollar operational decisions as they are working on industrial equipment. The workers can interact with the AI agents to get recommendations of machine performance, get the confidence levels coming from the machine based on data or get predicted costs based on data from the machines.
But the workers are making these judgment calls out on the line. So, the story that we see at GE and a number of other companies is not about efficiency at all, it’s really about reimagining processes in ways that weren’t possible before. GE says that they have moved from routine maintenance to unique maintenance, where workers are empowered to make these powerful decisions out on the line. That story, and the story that we have been hearing again and again, isn’t simply one of efficiency, it’s one of innovation and imagination.
Knowledge@Wharton: You examine how this reimagining will impact various elements of the business structure, including the supply chain. Can you talk about that?
Daugherty: We think the supply chain is a massive area of impact for artificial intelligence along with other technologies. We see warehouses, distribution centers and logistic centers being transformed through the use of AI — better receiving goods and understanding what is received into the warehouse, storing them more effectively so that they can understand the stock and pick goods to be shipped more efficiently.
There are many implications like that in warehouses and in logistics and that part of the supply chain. Then you think about the transportation part, getting things where they need to go faster. You have tremendous potential there as well to dramatically rethink and reimagine the way your supply chain can work so you can get those goods to consumers more effectively.
One of the things that we see with AI is a personalization in whatever part of the business you apply it to. In the supply chain, it’s being able to personalize the way you get the product to the customer faster. A great example of this is Stitch Fix, a very innovative retailer that uses AI to understand what you might want to buy, then has personalized fashion advisers who look at those recommendations and create a specialized clothing package just for you that they then ship it to you.
That requires a very different design process, a very different assembly of the products, a very different supply chain and distribution process to get something that personalized to the consumer. It’s a great example of human plus machine, where the human is using AI to better understand what the customer wants.
Knowledge@Wharton: Traditional retailers have been hurt by this digital shift. What do they need to do to keep up with the changes in the marketplace?
Wilson: Companies really need to start rethinking jobs around what we call the missing middle. One thing that we see in our research is that about two-thirds of executives these days are scratching their heads. It might be in retail, it might be in some of these industries that are being affected by automation. They’re scratching their heads and asking, “what new types of jobs are we going to need in the age of artificial intelligence? How do we change and retrain our current work force for the age of AI?”
Almost 30% of executives and senior HR leaders already have a bit of experience rewriting job descriptions for the age of AI, as we see in our research. So, we’re really beginning to see fundamentally new types of jobs that are being augmented by AI.
For instance, Walmart recently started rolling out robots that work in the aisles alongside associates. In a lot of ways, they are augmenting the associates. The robots go up and down aisles and scan for inventory and look for missing items, which are things that the associates used to spend a lot of time doing. Now, associates can spend more time interacting with customers, answering customer questions, running into the back room and getting things for customers that they couldn’t find in the aisles.
“Companies really need to start rethinking jobs around what we call the missing middle.” –James Wilson
Knowledge@Wharton: How has AI changed marketing?
Daugherty: That’s where we see a lot of activity right now with clients across a number of industries — financial services, retail, consumer goods, etc. — as they look at reimagining their front office in terms of how they interact with customers. As companies use more chat bots and virtual agents to help offload and answer some customer questions, and to help human advisers better serve customer needs, the way that the chat bot or virtual agent responds really represents the company.
It gets into what Jim said earlier about the new categories of jobs. We’re hiring people at Accenture right now, and we see need for more of what we call personality trainers for the AI we’re developing. How do you make sure that that chat bot or agent that you are using in your company embodies the brand, the values, the way you want to interact with your customers, and that you get the business result that you want? I think the big question for companies to think about as they deploy technology is, if AI is positioned to become the brand of your company, how are you developing it?
Wilson: The marketer today is empowered like never before. We have been doing research on this trend toward the democratization of AI, where it is getting easier and easier to use AI tools. A marketer now can upload a data set to a cloud platform and start doing some powerful analyses using AI that wasn’t possible before. Cluster analysis, classification, anomaly detection, doing customer segments in ways that really weren’t possible before.
We’re seeing that marketers and sales are becoming empowered thanks to AI, and we think this trend is going to accelerate over the next two to five years.
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Anumakonda Jagadeesh
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An AI takeover is a hypothetical scenario in which artificial intelligence (AI) becomes the dominant form of intelligence on Earth, with computers or robots effectively taking control of the planet away from the human species. Possible scenarios include replacement of the entire human workforce, takeover by a superintelligent AI, and the popular notion of a robot uprising. Some public figures, such as Stephen Hawking and Elon Musk, have advocated research into precautionary measures to ensure future superintelligent machines remain under human control. Robot rebellions have been a major theme throughout science fiction for many decades though the scenarios dealt with by science fiction are generally very different from those of concern to scientists.
Advantages of superhuman intelligence over humans
An AI with the abilities of a competent artificial intelligence researcher, would be able to modify its own source code and increase its own intelligence. If its self-reprogramming leads to its getting even better at being able to reprogram itself, the result could be a recursive intelligence explosion where it would rapidly leave human intelligence far behind.
• Technology research: A machine with superhuman scientific research abilities would be able to beat the human research community to milestones such as nanotechnology or advanced biotechnology. If the advantage becomes sufficiently large (for example, due to a sudden intelligence explosion), an AI takeover becomes trivial. For example, a superintelligent AI might design self-replicating bots that initially escape detection by diffusing throughout the world at a low concentration. Then, at a prearranged time, the bots multiply into nanofactories that cover every square foot of the Earth, producing nerve gas or deadly target-seeking mini-drones.
• Strategizing: A superintelligence might be able to simply outwit human opposition.
• Social manipulation: A superintelligence might be able to recruit human support, or covertly incite a war between humans.
• Economic productivity: As long as a copy of the AI could produce more economic wealth than the cost of its hardware, individual humans would have an incentive to voluntarily allow the Artificial General Intelligence (AGI) to run a copy of itself on their systems.
• Hacking: A superintelligence could find new exploits in computers connected to the Internet, and spread copies of itself onto those systems, or might steal money to finance its plans.
A computer program that faithfully emulates a human brain, or that otherwise runs algorithms that are equally powerful as the human brain’s algorithms, could still become a “speed superintelligence” if it can think many orders of magnitude faster than a human, due to being made of silicon rather than flesh, or due to optimization focusing on increasing the speed of the AGI. Biological neurons operate at about 200 Hz, whereas a modern microprocessor operates at a speed of about 2,000,000,000 Hz. Human axons carry action potentials at around 120 m/s, whereas computer signals travel near the speed of light.
A network of human-level intelligences designed to network together and share complex thoughts and memories seamlessly, able to collectively work as a giant unified team without friction, or consisting of trillions of human-level intelligences, would become a “collective superintelligence”.
More broadly, any number of qualitative improvements to a human-level AGI could result in a “quality superintelligence”, perhaps resulting in an AGI as far above us in intelligence as humans are above non-human apes. The number of neurons in a human brain is limited by cranial volume and metabolic constraints; in contrast, you can add components to a supercomputer until it fills up its entire warehouse. An AGI need not be limited by human constraints on working memory, and might therefore be able to intuitively grasp more complex relationships than humans can. An AGI with specialized cognitive support for engineering or computer programming would have an advantage in these fields, compared with humans who evolved no specialized mental modules to specifically deal with those domains. Unlike humans, an AGI can spawn copies of itself and tinker with its copies’ source code to attempt to further improve its algorithms(Wikipedia).
“ During the last century, the world shifted from manual labour to a situation where manufacturing is almost completely automated. 15 years ago, I was working at a company creating computer vision systems, replacing manual quality control in factories. Quality control by visual inspection is a task people are quite good at – at least, for a short period of time. It is difficult for people to stay focused for very long, and suddenly they drift off thinking of what to do in the weekend.
Computers are quite the opposite. They never take a break, and can focus on the exact same task 24/7 without ever drifting away. On the other hand, people have quite an astonishing real time neural network in their brains for pattern matching, and can easily spot errors. Visual inspection / quality control using a camera system and a computer is a difficult task to the extent that it has been one of the last areas in manufacturing to automate.
With advances in processing power and artificial intelligence computers can take on more and more advanced inspection tasks and the performance gap between humans and computers is rapidly decreasing.
Solutions using artificial intelligence will most likely increase productivity manifold in the coming years by automating more and more advanced tasks. To keep jobs, it is important that companies quickly adopt this technology and take advantage of these new opportunities. Embracing AI does not mean being replaced by machines. It is more likely that it will increase human productivity and thereby help both humans and nations to stay on top in the productivity race.
Conventional automation during the last hundred years has conquered almost all areas in manufacturing. In order to continue increasing productivity and hence stay on top in the productivity race, companies and nations will need to embrace the possibilities that AI promises.
AI is not a threat that will increase unemployment, but rather a technology that can ensure that our jobs will not be moved to low-cost labour countries. Investing in cognitive automation for manufacturing will increase the productivity of workers and therefore also secure the jobs in engineering and R&D”( Why AI Is Crucial To Increase Productivity And Decrease Unemployment, Oscar Sverud, APRIL 13, 2018 , AI Business).
Dr.A.Jagadeesh Nellore(AP),India