There’s no big bad Artificial Intelligence wolf, it’s the human that’s the problem
“Eighty per cent of the economy is getting transformed by Artificial Intelligence as we speak.”
– Dr Anastassia Lauterbach, author of The AI Imperative.
It’s clear that the scope for AI is huge. But what most concerns people is its future role in the economy and the shortage of skilled talent. How will it be utilised by businesses and corporations? How severe is the threat to job security? And will it really transform the future of business?
Although many of these questions still remain unanswered, what we do know is that AI is already being employed in various forms, by a wide range of businesses. AI is being used to sift through huge data pools, process applications, spot anomalies, draw conclusions and make informed decisions. The result is an increase in service quality and delivery – all while reducing cost.
The diversity imperative
AI is increasingly part of our everyday lives, present in everything from social media to home assistants like Siri. But what do we do if this hugely important technology is unintentionally, but fundamentally, biased? What are we going to about the fact that this hugely important field has almost no diversity? Without diversity, we cannot address problems that are faced by the majority of people in the world. 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.
Dr Lauterbach (Senior Advisor on AI and Analytics with McKinsey) states that “…in AI the diversity situation is very, very bad”.
So You Wanna Be In AI? is working with leaders in the field to address the current situation. And it’s not just about race or gender. In 1825 global literacy was at 20%. In 2018 the global literacy rate for tech is around 5%. That’s the big picture.
“The battle for diversity is vital, just from the perspective of finding the best talent in the widest possible pool. Demystifying the idea that AI is something very difficult is crucial, you do not need to code like Sergey Brin, the co-founder of Google. Being unafraid of a strange discipline is key. There is a huge gap between STEM and the arts and we need each other,” says Dr Lauterbach.
“Literally, there is no such thing as Artificial Intelligence,” she argues. “The phrase Artificial Intelligence is misleading because everything happens by human design. Human beings pick big data sets, algorithms, methodology and processing hardware.” According to Dr Lauterbach, if algorithms are not created to be inclusive, they could contribute to inequalities and thus would not be effective in helping the world.
“AI has a capability to scale everything we are about as humans,” she says. “So if you have a team of only white male developers or only Chinese male developers, then you will get a data set or some algorithms that are wired according to the preferences, habits and thinking processes of those groups.”
The entertainment industry gets smarter
The terms “artificial intelligence” and “machine learning” are used interchangeably. The former concept has its roots in the earliest days of computing, when the idea of a self-teaching and self-programming computer was first conceived. From Hollywood came films like The Terminator, Blade Runner, and The Matrix.
The entertainment industry is one we’re all familiar with and AI has already transformed our experience. Market leaders like Netflix tap into massive pools of viewer preference data to build algorithms that recommend new viewing material, and these algorithms leverage AI to learn what you’ll enjoy most. The process improves every year, and many users have no idea that the technology even exists.
Recently, filmmakers asked IBM’s Watson to analyse 100 trailers and use the visual and audio data to select scenes for a trailer — saving hours of time and input by human editors. AI is being given creative control in everything from journalism to advertising and it is now being used as the framework for user customised virtual reality experiences, interactive programming, and new methods of postproduction.
AI will affect much more than your Netflix home page. The prevalence of big data in nearly every sector means that technology can be used to improve just about everything we interact with on a daily basis. This new age of integrated AI is right around the corner, and most of us have already contributed our own data to the equation. Health care, global climate change, transportation, and scientific discovery are all transforming with the help of AI and ML.
Brands, AI and all that tech
As AI begins to shape our daily lives, brands must consider how they shift their behaviours and interactions to meet customers’ evolving expectations.
Consider how many marketers suddenly thought they absolutely needed a mobile app. This was a misconception – but it ushered in the importance of simplicity and utility in brand experience. The “app mentality” forced brands to take a hard look at their products and services and shape them to be fast, nimble and mobile focused.
We’re already seeing similar misconceptions about how and when brands should experiment with AI. Brands will need to think beyond creating experiences they want people to adhere to and start thinking about creating behaviours they want people to adopt.
The human factor
“I am a fan of how Alexa can request an Uber or how Netflix recommends what I like to watch. But, I am regularly irritated when a Facebook algorithm serves me ads for an entire industry because I accidentally clicked on the page,” says Will Shaw, producer of Siegel+Gale’s experience team.
“On the other hand,” he adds, “Mattel’s Aristotle audio assistant engages children, answering their questions through a conversational speech format built to understand young voices. Google has trained neural networks to recognise doodle drawing in real time. These brands break down the barrier between human and machine to form a seamless relationship across mediums, prioritising their audience’s needs.”
The move towards commoditisation of machine learning offers brands – and individuals – machine learning applications and projects with minimal expense. IBM’s Watson, Amazon’s AWS, and Microsoft’s Azure and others, offer suites of services for developers.
These cloud services provide a great deal of processing and computational power, so that product teams can switch from designing algorithms and machine learning to providing data for product design.
Training and the skills gap
Survey results show that 8 million workers in the UK have not participated in any learning at work in the last year.
That amounts to over a quarter, 26 per cent, of the UK workforce that has not recently taken part in career training and development.
“Complacency will be the difference between the UK’s workforce experiencing a digital shock or a digital revolution. As the UK debates the best path for Brexit, businesses and employees need to wake up to career complacency and help to solve the productivity problem.”*
* 16.3 per cent below G7 average
Added to this is the fact that 37 per cent of respondents said they don’t even feel they need to improve their skills. The UK needs not only to solve this skills gap, but the attitude of the workforce in relation to the future. Source: Association
This is why diversity in AI is an absolute imperative. As Professor Fei-Fei Li, associate professor for AI at Stanford University notes: “the lack of diversity among companies creating AI is a bias in itself.” AI isn’t just machine learning, AI scales up through brute mathematics what the human has designed – complete with bias.
Recent research by the MIT Media Lab has shown that facial recognition systems were accurate 99 per cent of the time when shown a photo of a white man but only between 20 and 34 per cent when the photo was of a black woman. Extrapolating from this one application of AI, it is easy to see that such biases could have profound implications when used in law enforcement, hiring and advertising.
So You Wanna Be In AI? joins So You Wanna Be In TV?, Film?, Creative? Banking? and Tech? driving new talent and diversity in the AI industry. It aims to open up opportunities to young people from financially disadvantaged backgrounds to help drive future proofing for business.
Collaboration is key. The private sector, regulators and policymakers must come together and combine shared knowledge. The answer to the lack of diversity of thought, innovation and talent lies in our untapped communities.
The more advanced the tech, the greater potential it has to influence our lives and therefore, the greater the need for us to ensure that the human element in its creation and development is as diverse as it can possibly be.
The more that diversity of thought and empathy is an intentional action within tech development, the more technology will be trusted by people. Diversity is not just a tick box exercise or a compliance issue, but actually the key to unlocking trust in the tech of tomorrow.
Join Rioch Edwards-Brown and a host of other speakers at Disruption Summit Europe.
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