It’s not news that technology has become an important factor in almost every aspect of our lives. More people are getting rid of traditional satellite TV and moving to streaming services, Alexa letting us know when to water our plants, and the average person spending almost 3 hours and 30 minutes of their day just on their phone. It’s safe to say technology is an essential part of our day-to-day lives.
It isn’t just limited to entertainment and convenience in our personal lives either; many of us could not do our jobs without technology. Whether we’re graphic designers whose entire role exists within a computer, to supermarkets whose tills use complex software to keep the shop running.
The Link Between Diversity, Inclusion and the Use of Technology
Our lives revolve around technology in many ways, which raises the question of why the UK is falling behind in adopting newer technology such as AI and deep learning in the workplace?
What if diversity in the technology industry is a related factor in whether or not your business will fall behind.
What does diversity have to do with technology?
A criticism often given to technology is that its level of diversity and inclusivity fall behind many other industries.
The technology sector is currently expanding 3 times faster than the rest of the UK economy, but the diversity numbers fall beyond other areas. Gender diversity is estimated at just 19% in tech, and this is compared to 49% in other industries. When you get to higher-level executive roles within the tech industry, gender diversity falls to just 5% of women in senior positions.
From a business perspective, McKinsey’s Diversity Matters Report found companies with high diversity levels are 33% more likely to outperform competitors.
There are four types of diversity that can be found in the workplace.
- Internal – These are things individuals are born with that are difficult or impossible to change, such as ethnicity, age and gender.
- External – Refers to characteristics an individual is not born with, but are shaped by their experiences and circumstances such as education and appearance.
- Organizational – This refers to whether organizations have a wide variety of job functions, union affiliations and work locations.
- World View – Dealing with the experiences that shape how an individual views the world, such as their political leaning or cultural background.
When a company looks to create all four types of diversity, they create an inclusive environment where there is no status quo on how an employee should look, or be. Research shows employees who feel they work in an inclusive environment work harder and are more likely to tackle difficult tasks with a positive attitude due to their sense of purpose and loyalty.
These varied issues don’t just lead to a better work environment — they lead to a better product.
How does diversity create a better product?
Timnit Gebru, a Microsoft researcher and co-founder of Black in AI, says the lack of diversity will definitely affect the development of artificial intelligence and progress in computers:
“There is bias to what kinds of problems we think are important, what kinds of research we think are important, and where we think AI should go.
When problems don’t affect us, we don’t think they’re that important, and we might not even know what these problems are, because we’re not interacting with the people who are experiencing them.”
Gebru’s argument is that because there is a lack of diversity within technology, there is a lack of diversity in the technology it produces, especially when it comes to complex artificial intelligence.
When we look back at only 19% of tech workers being female and how Apple’s first promised “expanse” health app tracked blood alcohol but not menstruation cycles, you can understand why a more gender-diverse team may have seen this addressed before public release.
For many people, adopting new technology can be difficult because the technology is simply not built for them.
We’ve seen soap dispensers with sensors programmed to only recognize lighter skin tones that simply don’t register darker skin tones. Then there is voice recognition, with many examples of people having to fake southern English accents so that Alexa can actually understand requests and statements.
If the newer technology can’t recognize your voice — this creates an idea that technology is not designed with a diverse society in mind. Therefore, it can’t be used by a diverse society. Some of the voice programs have AI — so it’s just a matter of ML that will eventually get your voice tones — so keep trying to be understood!
A Microsoft report shows only half of UK employees use AI to work faster, compared to 69% of employees worldwide.
The demand for AI and deep-learning technology is not going to slow in demand anytime soon.
Industries increasingly see uses for it, not only to solve complex data problems but to predict customer behavior and habits. However, only 32% of UK employees actually feel their workplace is doing enough to prepare them for the growing necessary use of technology.
Technology relies on not just testing in developmental stages, but real-world applications to evolve and improve.
With the UK’s slow adoption rate of some technologies, it limits a technology company’s ability to fully realize the potential of some applications.
When you look at technology through the lens that it may not be made for you, and therefore may not work for you — it becomes easier to see why people have a negative bias towards it in some countries.
Is there any way diversity and technology can work together?
Part of why it’s important to be critical of technology is because it’s become so important to us, and we’ve seen the incredible work it can do with regards to diversity and inclusion.
One of the many ways technology can improve diversity and inclusion in the workplace is through dedicated diversity and inclusion technologies. 43% of D&I technologies are used for the purpose of talent acquisition, including candidate sourcing and selection, and the key to many of these technologies is artificial intelligence.
Artificial intelligence can help remove unconscious bias in recruiting throughout the entire hiring process.
AI has actually been used to write job postings, where it can write factual descriptions without leading statements or biased language that could be seen as exclusionary.
We’re also seeing AI being used in applicant screening, where it can be programmed to ignore demographics like race, age – all of which have been shown to give candidates an unfair disadvantage whilst applying for jobs.
Research shows applicants with “white-sounding” names have a 25% chance of being called for an interview, whereas applicants with “BAME-sounding” names only have a 10% chance of being invited to interview.
AI will screen CVs without registering this information instead of focusing on relevant skills, experience, and keyword matching to ensure it’s the best talent for being interviewed for roles.
Technology can also be used to improve existing problems in the workplace, not just focus on finding new talent. We’re seeing increased use of intelligent automation in employee benefits and compensation.
By combing through multiple sources, a cognitive bot can offer accurate insight into the compensation and benefits patterns across your organization, giving an unbiased view of gaps across your workforce and creating an even working environment.
Technology has its part to play
Compared to many industries, technology as we know it is an incredibly new industry. But, it’s important to note that while it still has a long way to go to become the diverse, inclusive space it needs to be to create the most cutting-edge technology, it is actively working towards this and helping support other industries in this pursuit.
The biggest takeaway is that technology is still a product of human design, which means it is not a completely unbiased creation.
If we want to create programs and tools that the wider workforce can adopt, it needs to be designed by groups that represent the wider workforce and can look from a variety of angles.
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