Digital inequality often manifests in people not having equal access to digital services, or not having equal skills in using such services.
In this rapidly changing world, algorithms steer the lives and choices of people more and more often. It’s important that services meet the diverse needs of different user groups, and that algorithms and AI neither favour nor discriminate against anybody.
At the same time, people must have equal rights in their access to digital services. But there is still a long way to go in achieving this.
By working together, we can ensure that different viewpoints and needs are not forgotten when digital services are developed. In building our digital future, we must ensure that services take the different backgrounds of people into consideration.
Citizens of all backgrounds use digital services, so the services need to be designed with diversity in mind. It’s important that we have versatile teams for developing services and algorithms, as designers influence technology with their personal backgrounds and attributes.
Diversity brings different viewpoints and ways of thinking. By embracing this, a company can make better decisions in every part of its operations. The different ideas arising from diversity and unbiased innovation breed services, products, and ways of working that better meet user needs.
Companies that promote diversity in their operations are also the most attractive employers. Diversity is a value that attracts new experts while building deeper engagement with the ones a company already has.
All this directly influences the success of companies. Diversity is essentially a competitive factor that ultimately affects profitability and value creation.
There are several examples globally of how a lack of diversity has led to distortions in coding and the development of technology. Often these problems are the result of the share of women working in the industry being too small.
Several digital services exploit AI and algorithms based on data. Any underlying omissions, mistakes or distortions may have a significant impact on the use of such services, especially when different types of users are objects of a decision made automatically by AI. For example, an AI-based recruitment tool at a popular online retailer automatically reinforced predominant bias and attitudes related to gender, and began to discriminate against women.
Cultural stereotyping and gender bias have also been experienced in translation services. For instance, the AI of a widely used translation engine automatically assumed that a nurse is a woman, even when it was not possible to derive gender from a personal pronoun. Distortions can also be found in several speech-recognition services that understand the voice of a man better than that of a woman.
The strengthening of diversity and equality is central to TietoEVRY’s core values and goals. As part of our responsibility plan 2021–2023, we published an ambitious goal for the future: our aim is to increase the share of women among our personnel to 40% by 2026, and to 50% by 2030.
In Finland, only around one fifth of technology-industry experts are women. They are part of a rising trend though – in the past five years the share of applicants to ICT studies has doubled. But there is a lot more to do before we can balance the distribution and attract more women to become experts in our field.