AI – Augmenting, Not Replacing, Human Intelligence

Rob High, IBM Watson 

Rob High is an IBM Fellow, Vice President and Chief Technology Officer, IBM Watson. He has overall responsibility to drive Watson technical strategy and thought leadership. As a key member of the Watson Leadership team, Rob works collaboratively with the Watson engineering, research, and development teams across IBM. Prior to joining the Watson team, Rob was Chief Architect for the SOA Foundation and member of the IBM Academy of Technology.

 

Capgemini’s Digital Transformation Institute spoke to Rob to understand how AI is permeating across organizations of all sizes and how it is being used.

What will be one of the biggest changes that AI will bring to everyday experiences?

This goes to some basic fundamentals of human–machine interfaces. If you look at the history of computing, for the last 70 years of modern computing humans have essentially had to adapt to the constraints of the computer. The human–machine interface has always been defined by constraints in how the computer is capable of expressing itself, from punch cards in the early days to sliders today. They are still largely defined by forms of interactions that are not natural to human beings. So, one of the benefits that AI can bring to the table is a much more natural form of interaction. If the AI is already able to understand our language, what we hear, and what we see, then the next logical step is for us to begin to improve the way that it interacts with us. This is an area that will be most interesting to watch when we think about the application of AI in solving real-world problems.

Helping people be better at what they do

How can large organizations benefit from AI?

The primary benefit comes from helping people who do things today, do those things better. One practical way is where AI helps you consider more sources of information in a world where the amount of information that we are exposed to is growing exponentially, and far exceeds the capacity for us to possibly consume and assimilate. If you are an organization that has a very large call center, for example, where you are having to deal with very large numbers of customers who come to you for support or advice, then having a cognitive system can help significantly. For instance, you can augment call center staff by offloading some of the more mundane tasks. Call center advisors can do a better job in answering clients’ questions and concerns by finding information that would otherwise be difficult to access. Cognitive systems can also help companies where there is significant diversity of expertise across the organization. For instance, doctors who have been in practice for 20 or 30 years will have built up a lot of expertise from seeing many more cases and variations on those cases in different patients. This expertise can be captured and democratized through AI.

Which industries are best-placed to benefit from AI?

Currently, the healthcare industry recognizes the need to get this kind of assistance for their cognitive processing. Doctors know that it is very difficult for them to keep up with the very latest advances in their domain. They have therefore reached out very aggressively to adopt systems that make better treatment decisions or improve their ability to diagnose. Among other industries, financial services definitely has an interest. For example, financial advisors spend a lot of their time researching different investment choices for their clients, and that is a process that requires a lot of reading. It requires going through a ton of information. The more that they can get assistance from the cognitive system, the more information they can assimilate to make better decisions for their clients. Retail is another industry where I believe AI can significantly enhance customer interaction.

Get the use case right

Where can AI provide most benefit? Are there specific categories of data where AI can have greater impact?

One of the unique characteristics that AI brings to the table – which traditional computing doesn’t – is its ability to look at, and understand, human expression. By this, I mean things like text or literature and audio and video. To date, this data that has largely been the unique domain of human expression, and this is where AI has a tremendous opportunity to make a difference. In general, any place that has qualitative information that, up until now, has largely been ignored because of the limits of computational systems to understand it.

How should organizations go about implementing AI?

I believe it is always important to start with the use case, because the use case is going to then tell you how much work you have to do to get ready and also something about the value that you will get from having invested your time and energy. When you have a use case that you are ready to invest in – and it is well defined, scoped, and targeted – then you begin to look at the most effective way of evolving through that use case. You start to think of the minimum viable product that you need to create in order to get started and yield some of the benefits. You start there and grow. But if you don’t have the use case, and you don’t know the value of it or the market conditions associated with it, that makes it hard to answer any other questions.

Most popular use case: the contact center

What do you believe are the top use cases for AI?

The most popular use case right now is in the contact center. There is just so much room for improvement in the customer experience, the abilities of the agents involved, and the relationship between the institution and its customers. I see that as being an area of massive growth in the world of AI. It dramatically transforms the contact center industry, but more importantly the relationship between institutions and their clients.

Bot first, or human first?

If it comes to deciding whether to deploy a bot, or a human, how should an organization go about it?

There are a couple of different schools of thought. One is that you always send your clients to the bot to begin with, but build into the bot the ability to detect when the user wants to opt out and go directly to human. This approach is similar to the evolution I think we have seen in the IVR space. Many institutions are now forcing you to their IVR, and then in the IVR there is an option to talk to a human. The other approach is to make that choice available as different entry points into your organization. So, for example, you could have a web page where you are selling a product, and you have a catalogue of all the products in your store, and you deploy the ability to both chat with a bot or chat with human being there and let the customer make their choice.

Some of that has to do with the nature of the customer base you are dealing with. For example, there are a whole category or people in certain parts of the world that prefer to deal with a chatbot. To them, it seems anonymous and also gives them freedom to ask what they believe are silly questions and not be judged by a human being on the other end. Older people under certain circumstances may prefer to talk to a human being. So, by giving them that choice, people can go for the option that is most useful and comfortable for them. The third case is when you always talk to human beings. In this case, you really need to give AI to the agent and help them do a better job serving their clients. The idea is to make their client service consistent, more efficient, and with better quality of information.

You don’t need to be an expert in AI to benefit from it

If finding AI talent is a significant challenge for many organizations, how should companies develop AI capabilities?

I don’t think you need to be an expert in the technology of AI to benefit from it. You don’t need to be skilled in AI, you need to be skilled in your use case. Now, that is not to say there aren’t going to be cases where you need to build your own algorithms. But I think there are a lot of things that people can do with AI services that enable them to support the use case without having to know all the details of how that AI works.

How do you see AI impacting on jobs in the future?

I think that there will be some displacement of jobs, but I think for every job lost, there will be many more jobs that are gained. The role of AI is not to replace humans, it is to augment humans. It is about helping us be better at what we do; it is not about doing what we do. It means that in every job that is out there, where there is room for improvement, there is going to be a room for AI to improve the job, and make people better at what they do. So, it will be incumbent upon people to determine for themselves whether they want to take advantage of the benefits of AI. If they refuse, they are going to be at some risk. But for everybody else that want to improve themselves, they are going to find that AI actually makes their job better and easier to perform at a higher level. In the end, it is really about how we augment human intelligence, not about how we replace human intelligence.

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