Artificial Intelligence will radically transform the way we do business in the future, and the way we live. That’s a strong statement, but I believe it’s true. So it’s important to dispel some urban myths and understand what it can and can’t do.

Firstly, what is ‘Artificial Intelligence’?

There is not one but many definitions of Artificial Intelligence (AI), and its scope remains fluid and evolving. Some people even state that AI is everything that has not yet been done, referring to the observation that as the tools we use daily become increasingly sophisticated, tasks previously considered as requiring ‘intelligence’ are now considered routine and get excluded from the AI definition. Think for example of a good spam filter, spell check or optical character recognition, all of which used to be considered revolutionary, but today don’t impress people anymore.

Accenture defines AI as follows:

‘A constellation of technologies that extend human capabilities by sensing, comprehending, acting and learning – allowing people to do much more.’ In other words, we put the focus on the ability of AI to complement and empower people instead of replace them.

Therein lies the key: If you only look at AI from the perspective of a technology that ‘can do it all’, it will fail and create problems within organizations and society. The added value of AI lies in its ability to extend human capabilities. People, not machines, are at the heart of this so-called Fourth Industrial Revolution.

A constellation of technologies that extend human capabilities

Why is AI catching on now?

While AI exists since the 1950s and a good number of the AI tools we use today have been around for a while, its adoption has grown exponentially in the last couple of years. There are multiple reasons for why AI is affordable, doable and available today:

  1. Computing power continues to grow and decrease in cost, making it possible to capture vast volumes of data and run increasingly complex machine learning.
  2. Data is growing exponentially and the Internet of Things and Big Data solutions are creating new data sets each day. The resulting ocean of data provides the ideal basis for training AI tools.
  3. AI software packages and toolkits are becoming increasingly available, often offered as plug & play solutions through the Cloud.
  4. Lastly, the open innovation aspect of AI means it is easier to gain access to leading AI thinking and skills. As a result, more and more people will be able to create a bridge between humans and these technologies.

 “As we reach the next level of these technologies, they must also bring businesses and people to the next level”

How mature is AI?

AI is not omnipotent or capable of replacing us. AI systems are trained for a narrow situation. In essence, they sense (capture data), comprehend (associate a meaning to them), act (execute an action or pass it on to another system, be that a robot or human) and learn (an essential catalyst of AI is the ability to learn from historical data in order to improve its future performance) for a specific activity.

With AI covering a broad range of very different techniques, we observe different levels of maturity in these different techniques. Currently, those most actively explored are often used in combination.

  • Natural Language Processing: An AI system that understands and uses language as used by humans without imposed structures, words or commands.
  • Chatbots & virtual assistants: Natural language dialogue based and machine learning enabled, these computer-generated ‘characters’ can converse with people and answer their questions, transforming the way of interacting with customers.
  • Machine learning: By leveraging data and experience to improve its performance, machine learning is used, for example, in fraud detection, claims underwriting, credit scoring and micro customer segmentation.
  • Computer vision: Focusing on safety, security, and operations by live capturing and analysis images and video materials. For example, assessing suspicious behavior, monitoring traffic or assessing car damage for insurance claims, which is currently a lengthy process involving multiple intermediaries.

We must not ignore our responsibility to use these technologies ethically

What about ethical questions?

There is no denying the added value AI systems can bring. At the same time, we must not ignore their power and with that, our responsibility to use them ethically. This means making sure people remain at the center (enhancement of human activities, new skills, re-training…); that algorithms are not discriminatory (for example, in loan or insurance decisions); that personal data is protected; and labor and employment laws are complied with.

As we reach the next level of these technologies, they must also bring businesses and people to the next level, empowering them and building a better future for society.

Curious to know more? In my next post, I will discuss where to start with AI as a business and share real life examples of how these systems are being applied now.

Can wait? Feel free to contact me for a chat!