There is no longer any doubt whether artificial intelligence will help us in the future with relieving us from mundane, time-consuming tasks, simply making our lives easier. However, there is a lot of controversy around the impact of artificial intelligence, and whether it will have a good or bad effect on the society in the “long run”.

The political newspaper, The European Sting recently featured a piece by Virginia Dignum, Associate Professor on Social Artificial Intelligence at the Faculty of Technology Policy and Management at TU Delf, addressing the benefits of AI, and how we need to think of how we view the negative sides to this new technology – will it really affect labour and social equality to the lengths predicted? And do we need to worry about killer robots?

Dignum believes that AI already is, and will continue to change our lives to the positive, improving human health, safety and productivity. The website predicts that we will see the most impact of AI in areas such as transportation, service robots, healthcare, education, low-resource communities, public safety and security, employment and workplace and entertainment, according to the 100 Year AI report. However, it is essential that these systems are introduced in ways that will build trust and understanding and respect human civil rights, the feature says.

Why Should We Be Positive?

There is definitely a lot to be positive about as an outcome of implementing AI in our society. Looking at self-driving cars it could potentially contribute to decreasing the current number of millions dying in car accidents annually. Yes, self-driving cars do cause accidents and deaths, but it has shown a significant decrease in road casualties linked to the increase in self-driving cars.

And yes, jobs will be lost, but if we think differently, we can see the potential of freeing up people to do more meaningful jobs that would hopefully give them a better life-value too. The article predicts AI to contribute to a redefinition of human values, which is highly necessary, also including how we understand work currently, as well as wealth and responsibility. The article breaks it down to three significant points:


It is essential to rethink the meaning of work with the introduction of AI, as jobs change, but so does the characters of jobs. “Meaningful occupations are those that contribute to the welfare of society, self-fulfilment and the advancement of mankind. These do not necessarily equate with current ‘paid jobs’ “, the website writes. AI has the potential to free us up for these occupations, and allow us to spend more time doing things that can improve our mental health, such as spending time doing things we want to, not what we have to.


Dunn believes that combined with the changing or work-roles, the view on wealth introduces a new view on economics and finance too. As a result to the technological developments over the years, mass production and mass consumption have become normal. Up until the recent years, it has become  more about having, introducing the “I am what I have”-mentality.

Developments in the technology industry, such as AI has the potential to change this, as it chooses openness over competition with open data, open source, open access and so on. Hopefully, the mentality of “I am what I share” will develop further, and this in combination with the changing of work-roles has the potential to change how we view wealth.


With the development of AI, and how it has gone from a tool to a “teammate”, Dignum deem the most important result of AI advances as the need to rethink responsibility.

“Greater autonomy must come with greater responsibility, even when the notions of machine autonomy and responsibility are necessarily different from those that apply to people. Machines are already making decisions”.

As machines are now making decisions we need to think of a higher level of responsibility, as responsibility contributes to trust which includes accountability and the ability to explain and justify decisions.

The ability to trust people lies in the ability to understand their actions, to “put ourselves in their shoes”, which is impossible for machines, hence why trust in machines must be based on transparency, the article writes.

In order to place human values at the core of the AI systems, there is a need for a mind-shift of researchers and developers aiming towards improving transparency rather than performance, which will subsequently lead to novel and exciting algorithms, “turning deep learning into valuable learning”.

Dignum says how she is positive about the future of AI developments, and emphasise how researchers and developers are ultimately responsible for ensuring that human values are at the basis of the design and implementation decisions.

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