Artificial Intelligence: A Harbinger of Business Innovation 0

Christian Guttmann

In an exclusive interview with All Things Talent, Christian Guttmann, Vice President, Global Head of Artificial Intelligence and Data Science at Tieto shares insights on how to drive a successful and full utilisation of AI for business, bridging the AI skills gap and experiments undertaken by Tieto in the area of innovation. He also shares his viewpoints on using technology ethically.

Christian Guttmann is the Vice President, Global Head of Artificial Intelligence and Data Science at Tieto. At Tieto, he is responsible for strategy and execution of Artificial Intelligence and Innovation. He is an adjunct associate professor at the University of New South Wales, Australia and adjunct researcher at the Karolinska Institute, Sweden. He is a veteran who has built and led the design and development of 100s of AI products and systems. He has dedicated his career and life to Artificial Intelligence and Machine Learning for over 25 years. Guttmann is an entrepreneur and co-founded startups where he led the business and product development using Artificial Intelligence technology. He has edited and written 7 books, over 50 publications and four patents in the field of Artificial Intelligence. He is a keynote speaker at international events, including the International Council for Information Technology (ICA) in Government Administration and CeBIT and is frequently cited by Nordic and international media, such as the MIT Sloan Management Review and Bloomberg.

JOURNEY

Q. You have dedicated 25 years of your life’s work and career to advancing Artificial Intelligence and Machine Learning. What inspired you to study Artificial Intelligence? What were your initial main challenges when you began to study Artificial Intelligence?

A. When I was a young boy, I was utterly fascinated by the thought of building something that could be smart and behave like an intelligent being. Early science fiction movies and existential books inspired my ambition, and I taught myself to program computers when I was 12 years old. I then went on to study psychology to learn why and how humans and animals behave and make decisions, and in parallel, I also studied the science and engineering of Artificial Intelligence. In my view, Psychology and AI were an excellent combination, as you cannot build what you do not understand. Psychology provided me with deep insights into the only things that we knew are intelligent, namely
humans and animals. And my knowledge of AI-enabled me to design and build intelligent systems.

A challenging part was to understand the enormous breadth and width of the AI field, which started as early as Alan Turing who wrote the book “Can machines think?” in 1950.

AI is perhaps the ultimate human endeavour to understand ourselves completely: how we think, feel, behave and make decisions in great detail.

As we continue to achieve AI breakthroughs, such as alpha-go zero, and grand challenges such as RoboCup, we will come closer to building general machine intelligence that could be similar in part to our intelligence, and possibly even more intelligent and emotional in many other parts.

ARTIFICIAL INTELLIGENCE

Q. AI is on the verge of becoming a critical part of business infrastructure. According to you, how will companies need to rethink their traditional business models in the face of the AI movement?

A. There are three factors that drive the successful and full utilisation of AI for business: creating an AI strategy, managing required business changes and trusting AI, and finally having an adequate IT and data infrastructure. The AI strategy includes a strong commitment from the leadership and a clear understanding of how the company will use AI to reposition itself in the emerging AI era, such as where it wants to compete and what capabilities it will need. Companies have to be very rigorous about this. The CEO needs to be ready to present the AI strategy to the board and articulate ‘this is how we are proceeding, and this is what we will be known for in 2022.’

The second factor constitutes the changes this strategy will bring in the company’s business processes and the trust key stakeholders need to have in AI. You can’t just build an AI product or service and drop it on the employees or customers. You have to think about how the business will run differently and how the company needs to change its routines. The other part of the business impact is trust in AI: you need your employees and customers to trust that AI will do what it is expected to do.

Finally, you need to make sure your company is data and IT ready. You need to determine how quickly you can access the relevant data or computational power to run the planned AI services. This is not trivial. Data native companies have the purpose of good data written in their genes but if you are a forestry company or a container ship company that has never had data in their DNA, it is likely that you are not sufficiently prepared. The average company has dozens if not hundreds of databases that are not connected. For a proof of concept (POC), ad-hoc data collection might just do the trick, but if you want to operationalize the AI services sustainably, you need the IT infrastructure to work smoothly so you can successfully use AI to optimize and predict. For that, you often need to have a data hub and this needs to be created before you make the AI processes part of the core process of your organisation. If this requires a major change then you need to bring this to leadership from the beginning.

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STRATEGY

Strategy

Q. When we talk about Artificial Intelligence and Machine Learning on strategy, innovation, and execution, what are some of the biggest initiatives/experiments you are currently working on at Tieto?

A. “Teams of teams” (ToT) is a concept that we have experimented with at Tieto in 2018 in a business unit called Customer Experience Management (CEM). ToT means that we enable the formation of individual teams in sync of market needs, and these teams are given authority to make decisions. The actions of the teams are faster, more agile and more robust than in traditional organisations. Due to the success of this concept, we now scale this broadly across the whole organisation. All of our 15000 employees are given more autonomy to proactively act too small and big market changes and customer demands.

The average company has dozens if not hundreds of databases that are not connected. For a proof of concept (POC), ad-hoc data collection might just do the trick, but if you want to operationalize the AI services sustainably, you need the IT infrastructure to work smoothly so you can successfully use AI to optimize and predict.

SKILLING

Q. Lack of human expertise has been found to be one of the biggest hurdles for AI implementation. In your opinion, how can skilling and re-skilling help to bridge the AI skills gap?

A. There are at least two major actions every business has to undertake to not missing the boat in the AI era.

First, your company needs to have an AI strategy, committed leadership and, a dedicated top AI team that acts across all business unit. Under these three conditions, your company will have a more likely success rate in adopting and driving AI development.

The second major action is then more practical: All employees need to learn about AI and machine learning. This will be done by setting an appropriate curriculum (according to the strategy and the Chief AI officer and his team) which can then be executed in the many online universities, like EDX, or Udacity. Second, this “book knowledge” then needs to take to the real test. To that end, you need a company-wide adoption.

Our AI can detect the risk of individuals becoming socially excluded and can reduce the huge burden of individuals and public health care cost associated with social exclusion. In general, the biggest challenges of using AI and machine learning are to alter the course of a person’s life, in terms of this person’s health, fortune or human rights.

Skilling

INNOVATION

Q. Let’s talk about technology and how it affects innovation. How is Tieto undertaking some unique experiments in the area of innovation? What challenges have you encountered so far?

A. With new fundamental technologies come great responsibilities. We have been utilising AI and machine learning across many industry sectors, including manufacturing, transport, retail, financial services, health care, and education. In all these sectors, our AI and Machine learning have the potential to improve business processes, decrease uncertainties and in some cases transform a corporate strategy. For example, we have developed the AI capability to predict the arrival of delivery trucks to stores, which improves the workflow of store employees.

Our AI can detect the risk of individuals becoming socially excluded, and can reduce the huge burden of individuals and public health care cost associated with social exclusion. In general, the biggest challenges of using AI and machine learning are to alter the course of a person’s life, in terms of this person’s health, fortune or human rights.

Tieto has introduced 5 AI ethical principles that shape our way of using AI responsibly. The biggest challenge or goal that we have set ourselves as Tieto is to set an industry standard when it comes to the best and most responsible use of AI. We assess every case carefully to ensure we achieve this goal.

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ETHICS

Q. New technologies bring new opportunities and new challenges. How do we ensure we use technology ethically, in support of what’s good, and minimize harmful pitfalls?

A. Ethics is a complex area – and I have started to realise that it will be highly unlikely, if not impossible to find universal ethics that everyone will agree with. There are so many different ethics and value systems that are carried by communities and by individuals, and it is very good that we have so many different viewpoints. However, I think it is unlikely that we find one common ethical denominator. I believe that we will find a balance of “benefit versus cost” of new technologies such as AI, something that I call minimal viable ethics. And in some way, we achieve this is how we have always done this, by an exchange of viewpoints combined with continuous scientific progress of the safety and usefulness of new technology for our society and human progress.

CULTURE

Q. A technology shift that isn’t backed up by a corresponding cultural shift can put the success of a digital business initiative at risk. According to you, what can be done to foster a company-wide shift in mindset and not just technology that will accelerate the transformation process?

A.

Right now we are not only facing a mere technology shift – technologies such as AI, IoT, 4D printing and blockchain have now initiated a silent revolution that is likely to reorganize our society and disrupt our economy bigger than with any technology before.

Think about how AI will influence any and all daily processes that each of us is part of – the way food is sourced and prepared, how we receive healthcare, how we are transported, and how we interact. This also influences the workplace and businesses. Employees will work together in ways never thought of, likely using AI assistants and robots as co-workers and team members. And the capabilities of a company will create services and products that are tailored for every customer in a speedy and accurate way. I think, by and large, we have not yet completely figured out what the required mindset is to prevail in this 4th industrial revolution. However, finding a common purpose with which every employee identifies with and can contribute to will be important. Equally important is to communicate this common purpose effectively to all stakeholders for the purpose of not only setting the right expectations but also to bringing the right responsibilities to individuals and teams.

Leadership

LEADERSHIP

Q. In this age of constant disruption, how pertinent is it for a leader to reinvent and transform continuously in the face of challenges?

A. It is important to find the right level of speed of the transformations in balance with the continuity that is required to run a business successfully and sustainably.

Transformation in the face of continuous disruption does not mean to change the direction of the company too often and too quickly. A leader is still a leader, which by definition needs to lead the way, do things differently based on his or her deep experience of the business, an intuition of technological and societal changes, and today more important than ever before, based on accurately judging the data-driven business.

A leader also needs to be capable of creating a resilient workforce with an agile and collaborative culture.

Quick Facts About Christian Guttmann

Hometown: Stockholm, Sweden – although I consider myself a global citizen as I lived on many continents during my career

Things He Values Most: Authenticity and individualism – too many just follow other’s ideologies and waste their lives

Passionate Pursuits: Towards creating Machine Intelligence for social and economic prosperity

Greatest Influence Growing up: My parents and scientist such as Richard Feynman

Sports He Follows: Surfing, and I love unspoiled nature

Favourite Books: Man without Qualities (Robert Musil), The Thirty-Six Stratagems (Sun Tzu), Siddhartha (Hermann Hesse), Im Anfang war der Wasserstoff (Hoimar von Ditfurth), Thinking fast and slow (Daniel Kahneman), and – this book is a great account of many main psychology experimental studies in social and psychology that I found essential in my career)

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