Should UK companies invest in AI?
18/06/2019 / Comments 0
It isn’t hard to see that Artificial Intelligence (AI) technology is becoming more and more prevalent in our everyday lives, even though industry experts assure us that what we are seeing so far barely scrapes the surface of the possibilities.
There’s no shortage of advice about how and when different businesses should be using and investing in AI. With a new report from McKinsey Global Institute claiming that UK businesses could risk losing 20% of their cash flow if they don’t invest in AI, it’s becoming harder and harder to ignore its influence.
But does that mean that all businesses should begin throwing money into the new technology at the drop of a hat?
Even the experts have to admit that the world of AI is complex, high-risk and for the large part unexplored.
To help you weigh up your approach to AI, we’ve taken a look at the current landscape, opportunities and risks that you should be aware of.
Why UK businesses?
When it comes to AI, the UK is fast establishing itself as one of the major players in innovation and investment.
In 2018, venture capital firms invested a whopping $1.3bn in UK based AI companies. In February this year it was announced that £200 million would be invested into new centres and to fund PHDs, while only last week the British government committed another £18.5 billion to boost diversity in AI tech roles and innovation in online training for adults.
It is hoped that this will ensure the UK remains ahead of the curve when it comes to artificial intelligence. And while other countries are also promising investment in AI, the UK has still remained a popular location for AI start-ups and already boasts a number of success stories.
AI start-up Magic Pony, which uses machine learning to turn grainy footage into high quality footage, was bought by Twitter in 2016 for $150 million.
Another UK start-up, Cognetivity, which uses AI to detect dementia in its earliest stages, recently raised over $4 million to commercialise its innovative technology.
With the number of success like these growing across the UK, it’s clear to see why it’s important for UK based companies to consider AI technology.
But how can your business get involved in AI, and more importantly, should it?
What are your investment options?
Depending on which sector your business is in, you will have a variety of different options when it comes to how you can invest in AI.
There are a large number of useful AI based solutions (and some less useful that simply try to cash in on the term!) on the market that you can deploy internally.
Different applications of AI may be useful to make your day to day operations more automated. For example, chat bots can be used for communications with customers, and other software can be used to automate simple admin tasks.
Some of the most common areas where businesses are using AI software include:
- Customer services
- Performance measuring
- Finance and accounting
- Marketing and Biz Dev
As well as looking into currently available technology for your business, there are other ways you could be investing in AI.
Depending on the services you offer, could there be a way to enhance your service or provide a new dimension in the future with AI? Look at what is currently being developed and see if it would be applicable to what you do. If you can get behind and invest in emerging technology early, it will give you a clear advantage over your competitors.
The potential risks of AI
If you haven’t embraced AI in your organisation yet, there are likely to be several reasons, not least of all the high price tag attached to a lot of these software solutions.
The practical considerations when implementing AI include long implementation times and the investment in training staff to use often complex technology.
Some of the most discussed concerns are ethical, and when looking into implementing AI it’s important to be aware of them, not only for your own peace of mind but also so you can reassure your customers and employees.
The loss in human jobs due to automated technology
A common concern is a reduction in employment as advanced automated technology takes over more and more jobs, starting at the lower end of the cognitive scale and working up.
While there is plenty of merit to the theory that AI will eventually cause a widespread change in employment, this will be a gradual change, and is realistically no different from the effect of previous new technologies that automated manual tasks rather than cognitive ones.
The effects of automation on human behaviour
By using and interacting with this technology, humans will see changes in their own behaviour.
One reason for this is the machine or non-human becoming the norm. You may see an example of this at a ticket office, where signs encourage you to interact with the cashier. As we become used to receiving tickets from a machine rather than from a real person, the way we expect to carry out this interaction can change.
There may be other effects on our behaviour, with attention spans, decision making and communication all being areas where we can expect to see shifts.
Machine learning bias created by humans
There are several stages during development where bias can affect AI technology.
First, when outlining the goal of the technology, many businesses won’t be focused on fairness and discrimination. For example, a loan provider who wanted technology that would help them maximise their profit margins may find that the algorithm created around this goal saw loans being offered to people who aren’t creditworthy.
When collecting data, bias can occur because the data you collect is unrepresentative of reality or because it reflects existing prejudices. Examples of this could include a face recognition system that was originally fed more photos of light skinned people, so was worse at recognising dark skinned faces. Amazon encountered a bias in their internal recruitment system. As it was using past hiring decisions (which favoured men) as data, it was dismissing female candidates.
Finally, bias can be introduced when preparing data. At this stage you are selecting which attributes you want the system to consider and what weight each attribute will hold. These decisions will influence the accuracy of the model but will also have an impact on bias which could be just as great and harder to detect.
Are you planning on investing In AI in the near future? What considerations did you undergo to bring you to your decision? We’d love to hear what you think in the comments below!