How can we avoid succumbing to AI skepticism in the workplace?

Sommaire:

1. AI skepticism

2. Situation today
2.1 the fear of AI  
2.2 its application

3. The Solution

1. AI skepticism

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"The development of artificial intelligence could spell the end of the human race," says Stephen Hawkings.

1.1 Artificial intelligence goes off the rails.
1.2 Conscious, intelligent machine development.

When we're confronted with the idea of 'futuristic' technologies like these, it's clear that many dangers are present and there are several topics to talk about. So it's entirely understandable that hundreds of thousands of people are opposed to its development and everyday use. This is highly problematic, especially in the world of work, since AI has proven to be an advantage for the companies that employ it - it enables certain processes to be automated, or even costs to be cut. So, how can we help a team to accept the use of AI, and what criteria should be put in place to make sure there are no dangers?

2. Risks that frighten companies

2.1 Cybersecurity and confidentiality

Although artificial intelligence is succeeding in helping cybersecurity, it can also be a vector for malicious attacks.Indeed, as technologies evolve, cybercriminals become more pervasive. We know that AI involves processing massive amounts of data. This opens up a wider field of attack for hackers. Other criminals are using AI-powered bots to perpetrate online attacks.What's more, the danger of artificial intelligence concerns the confidentiality of certain information. Indeed, AI can learn to know you and predict your next purchases, by observing your searches on the Web, as denounced in the film "The Great Hack".

2.2 Cognitive biases in algorithms

Among other controversial subjects, AI is also the subject of controversy over racial and sexist biases and prejudices of other kinds. Even if intelligent systems themselves learn to predict outcomes, they rely on data and algorithms. However, the data used is collected by humans with conscious or unconscious biases. In other words, AI solutions, although they don't require human intervention, remain above all a reflection of the data, which in turn reflects humans and their history. As a result, the results obtained are not always effective. What's most deplorable is the fact that those most affected are usually the marginalized. In the case of healthcare, for example, this would mean that some patients don't get the right treatment, or are put on longer waiting lists.These risks are the reasons why 40% of companies have not yet adapted AI and have no plans to do so.

3. The solution

In order to overcome these risks and your employees' fear in relation to AI, we have grouped together these 4 categories, which we consider to be essential to this. Once adapted to your AI solution, your team will be much more apt to trust the new technology.

3.1 Transparency

When we use the term transparency, we're talking about the fact that none of our freedoms should be called into question. We need to be able to continue to make our own choices and feel free. So we mustn't let AI deprive us of this.

3.2 Explainability

This means that all the different functionalities employed by AI must be explainable. In addition, the answer to the question must be clear and obvious to the whole team: Why are we using AI and what is its importance to our company? If an employee doesn't quite see why, it's very important to make it clearer.

3.3 Fairness

As we saw earlier, one of the biggest risks of AI is the inequality provided in these choices and decisions. Since the data fed into the algorithm is biased, so are the results it produces. We must therefore be certain that the initial information is accurate, to ensure that the AI's judgment remains impartial.

3.4 Privacy

The subject of privacy evokes everything that is not related to professional life. In the workplace, I may not want my colleague or manager to know about certain aspects of my private life. We have to make sure that AI doesn't infringe on this.  Another solution for adopting AI into business operations is simply to get started. After all, we know that 56% of companies in Europe have implemented a pilot containing AI, and that only 4% of these have subsequently refused to implement it!