The need for a long-term AI strategy

Lili Cheng, Microsoft

Lili Cheng is a Distinguished Engineer and Corporate Vice President of the AI and Research division at Microsoft. Lili is responsible for Microsoft’s AI Developer services such as Bot Framework and Cognitive Services. Lili founded the Social Computing Group in Microsoft Research & Future Social Experiences (FUSE) Labs, was the Director of User Experience for Microsoft Windows, and innovated on technical infrastructure in the areas of real time data and search.

Prior to joining Microsoft, Cheng worked in Apple Computer’s Advanced Technology Group on the User Interface research team, where she focused on QuickTime Conferencing and QuickTime VR. She has also taught design at NYU and Harvard University.

Capgemini’s Digital Transformation Institute spoke to Lili to understand her views on AI and what it means for large organizations.

Experiment, experiment, and experiment

How can AI help large organizations?

We believe there are two broad areas. One is about B2C and the other is about how people get work done inside a company.

Let’s start with the first area. For example, if I want to interact with my insurance company today, it is still pretty hard to get basic help for some of the tasks that I want to do. One area we have been focusing on therefore is customer support: helping companies answer both simple and more complex questions and working with them to improve the way they reach their customers.

The other area is how people get work done inside their companies. We are focusing on how people work on projects, manage email, schedule their meetings, communicate via messaging, and so on. We believe AI can be of significant help here. Take this very discussion for instance. We should be able to have a more dynamic way of understanding the context quickly. I need to go into my mail, find the right email, and quickly look at a couple of other things before I come into the discussion. Then, we have to figure how to record this interaction and take notes and follow up. People spend so much time in meetings and it it’s an area of dissatisfaction for many because they often feel it’s not the best use of their time. We are thinking about how to improve the intelligence when people come together in groups.

How should large organizations approach AI?

The rate at which companies and researchers are sharing and open sourcing their technology is really unprecedented. It is great because it means you will have more people who actually have domain expertise and can author and create intelligence. We don’t want people to have a PhD in AI to benefit from it. The tools need to be usable by people with different skill levels. The person actually using the tool is probably one of the best people to design it.

What are some of the areas where AI can have the most impact?

The areas where we think companies will want more intelligence is in managing the financial data flow – who your customers are, what they are doing, who has paid their bills and so on. Customer support is obviously a big area and another really interesting area is time management. We recently acquired a start-up called VoloMetrix. They look at workplace satisfaction: how people spend their time; how satisfied they are with their job; how much time do they spend on meetings and email and what is the best way to help people be more proactive and spend their time more meaningfully? In a certain sense, computers have taught people to be very distracted. One of the things that could therefore be really interesting is how AI can help people manage their time more effectively.

What should organizations bear in mind when they deploy AI solutions?

The one thing you need is simply better data. Having the data so that you know where you are and the top three scenarios for where you want to be.

Being able to experiment quickly with some customers before building the entire system is also really critical. This is because if you want the perfect AI solution it can take a while to get all your data, integrate it and roll it out. Also, there’ll be times when the things that your customers want are going to change. A year ago, for example, people were a lot less interested in speech. Today, I think people feel the need to not just have text-based solutions, but also speech-based solutions. So, I think being able to experiment quickly, and have an experimental group that can try things out ahead of the entire organization will be crucial.

How should organizations decide what should be driven by a bot versus what should be driven by a human?

When you first roll out your system it is not going to be very smart because it doesn’t have that much data. In the beginning it’s therefore particularly important that you have people to override, train and manage the system. But over time, as the system learns, then we can project with high probability that this task can be automated. At that point you can automate it and your people can focus on complex tasks, new areas, or things that are more ambiguous.

We are better prepared for the onset of AI than any other technology in the past

AI will likely impact on jobs. How do you believe organizations should approach it?

I think that organizations should know that their people are probably their most valuable asset. Without your employees and your customers, you don’t have a business. So, making sure people’s jobs are interesting is really critical. I also think it’s really important to be aware of why you are automating and which new opportunities you need to go after. We have been focusing more on areas that are still fairly hard to automate and, so I don’t think that we are seeing job displacements. But I do think that it’s something that companies and governments need to work on together to ensure we all understand the impact.

What do you see as the future for AI?

It’s important to remember that every technology has changed the workforce. If you think of the Internet, the ability to access the world’s information instantly has changed a lot of jobs. With AI, compared to other technologies, we are probably more mindful of the impact on how work may change. I think it is our responsibility to make sure that it is augmenting how people work. We need to ensure that people can spend their time more effectively and we are really committed to that. We are all thinking a lot more about this than we thought about, for example, the Internet. We didn’t have these conversations when the worldwide web was emerging, because I don’t think people really had the foresight to think about how it was going to transform the way everybody works and lives. This time around with AI we are a little bit smarter to be asking these questions earlier.

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