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What are the pros and cons of AI?

We weigh up the benefits and the negatives of the technology that's changing business

​Artificial intelligence (AI) as technology has long been associated with science fiction, at best a long way off from revolutionising our lives and at worst the building blocks for the like of HAL 9000. Now that it is tentatively here, AI has a range of uses in the present and offers great potential for future innovation.

In many ways, it is still an immature technology, with plenty of room for improvement. Despite this, the past decade has seen a great increase in the use of AI to perform simple tasks, and the use of technology in all sectors has exploded since the start of the century. Smart home assistants are driven by AI - a common example of AI existing in the consumer space - but industrial applications are also nearly as ubiquitous.

The way businesses are deploying AI has been at times very impressive, while at others has prompted concern. The best examples of both AI’s highs and lows come from its use by businesses, rather than consumer products — so no need to unplug Alexa just yet.

AI use cases

Moving further up the use scale, we have standout names like Watson and AlphaGo. These are systems that have already proven they can roundly beat even the most accomplished human competitors, with a poker-playing AI being the most recent example, beating five professional players at once.

While these types of feats may seize the newspaper headlines, the majority of AI use today is still quietly slogging away in the background.

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If you use Google's email service Gmail, you may notice that it will now show the text as you're typing. Replying to an email from Sarah, it will suggest her name as soon as you've typed "Hi" or got partway through "Hello". It will offer other suggestions (such as "are you?" if you start typing "How" in the first sentence or two) as you go along and change them on the fly as you're typing out sentences.

A key use case of AI is mining data to help businesses, NGOs, governments, and others make informed decisions on everything from strategy to product development, and to do so much more quickly than ever possible before.

But that's just scratching the surface of AI's potential. Indeed, it's being used in myriad sectors and scenarios, many of which are explored below.

Like all technologies, however, it's not a neutral force, and there is always the potential for negative outcomes and benefits in equal measure. The late theoretical physicist and cosmologist Stephen Hawking famously believed that AI presents an existential threat to humans, and many experts have voiced concerns over the severe risk presented by improper use.

So is AI a force for good? Or is it something we should be inherently distrustful of?

The pros of AI

AI is going to proliferate over the next few years and likely beyond that, too. The applications of the tech are far too impressive, efficient, and cost-effective for businesses to ignore which means the amount of AI we interact with daily will increase in all areas of life. What’s more, it’s becoming safer. Algorithmic biases are still problematic, for example, but innovative work is being done to make AI better for everyone.

Improved efficiency

Data is now as important to business as oil once was, and there is a necessity to process this data accurately and quickly for real-time results. A great example of this type of artificial intelligence is being utilised by DeepMind to diagnose sight-threatening eye conditions with the same level of accuracy as the world's top clinicians.

Alongside UCL's Institute of Ophthalmology and London-based Moorfields Eye Hospital, their research could lead the way for the rollout of AI systems in hospitals throughout the UK. Thanks to the AI system, doctors can spend less time studying thousands of eye scans and can help diagnose patients within seconds.

Eradicating human error

Even the best of us are prone to errors, whether it's a lapse in concentration or a simple mistake. However, an artificially intelligent machine built to carry out a specific task does not display these idiosyncrasies.

Technology giant Amazon has recently begun to roll out fully autonomous robots in its fulfilment centres, which can work alongside humans to perform physically-difficult manual labour and sorting of packages. It’s possible that this could make Amazon warehouse work a lot safer. A 2021 study by the union coalition the Strategic Organizing Center (SOC) concluded that 5.9 out of every 100 Amazon warehouse workers experienced serious injuries in 2020, a rate just under 80% higher than at other warehousing employers.

Smart technology

Similar to Amazon, AI will be utilised in the future to power many of our automated services. These could be smart cities that are predicted to improve our environments, or self-driving cars that use AI to navigate roads and assess obstructions.

An AI machine's ability to process large data sets quickly and accurately will be vital for many smart technologies and environments to operate. An example of this is already in operation on many top-range smartphones, where AI operates in the background constantly tweaking the phone's settings for maximum performance or battery life.

The cons of AI

It’s natural to be fearful of powerful technology. Recent history with data scandals, malware, and social media has made that clear. AI is no different and many of the concerns held by onlookers are, in some areas, justified. But that doesn’t mean great work isn’t being done to mitigate the drawbacks.

In 2016, an industry-wide organisation including five Silicon Valley giants was formed, known as the Partnership on Artificial Intelligence to Benefit People and Society. This body works to promote the fair and ethical development of artificial intelligence technologies that have the potential to bring as much disruption as it will benefit.

Decision-making AI in the workplace

The speed and efficiency of certain AI applications make them appealing to executives looking to find more value across their organisation.

IBM's Watson has been used to decide if employees are worthy of a pay rise, a bonus, or a promotion by looking at the experience and past projects of employees to indicate the future qualities and skills individuals could bring to the company.

Decision-making software used in this way has caused some concern. The Trades Union Congress, the federation that represents the majority of trade unions in the UK, called for legislative changes last year to safeguard employees against this kind of technology. It is also recommended that employers consult trade unions before deploying such systems.

"Our prediction is that left unchecked, the use of AI to manage people will also lead to work becoming an increasingly lonely and isolating experience, where the joy of human connection is lost," TUC general secretary Frances O'Grady said.

Job losses

The potential for human job losses is widely regarded as the number one downside to AI, the implementation of which could set in motion a wave of lay-offs as employees struggle to outperform machines. 

However, while this scary scenario is often presented as just over the horizon, AI is expected to create more jobs than it takes. The World Economic Forum’s (WEF) 2020 Future of Jobs Report predicts that by 2025, automation will have affected 85 million jobs around the world but 97 million jobs will be created in industries such as artificial intelligence.

“No matter what prediction you believe about jobs and skills, what is bound to be true is heightened intensity and higher frequency of career transitions, especially for those already most vulnerable and marginalized,” stated FutureFit AI CEO Hamoon Ekhtiari.

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The report also stated that, although the pandemic has accelerated the automation of many repetitive and dangerous tasks, “around 40% of workers will require reskilling of six months or less”. One area of skills worth developing in time for the AI-based future is data, but soft skills shouldn’t be ignored either. John Whittingdale OBE, former minister of state for media and data, described soft skills as “hugely important”, adding that, “without them, there is the potential for data to be misread or miscommunicated, which can have significant implications for businesses and the decisions they make”.

Human error

Although AI can virtually remove human error from processes, its code is still subject to bias and prejudice. Being largely algorithm-based, the technology can knowingly or unknowingly be coded to discriminate against minorities or fail to cater to groups that its programmers failed to consider.

If security measures are not followed carefully, hackers can exploit AI seeking to collect public data. For example, Microsoft's ill-fated chatbot Tay Tweets had to be taken down after only 16 hours as it had started to tweet racist and inflammatory content driven by input from other Twitter users.

Importantly, Tay Tweets was purposefully fed hateful content in an effort by Twitter and 4chan users to break it. But other examples of AI going astray have come despite the best efforts by its developers. 

For example, in 2018 Amazon decided to retire a recruitment algorithm after it was discovered to discriminate against non-male candidates. The AI system was intended to provide hiring recommendations and had been fed ten years of application data to help train its decision-making. However, as the majority of submissions have been handed in by men, the conclusion the AI came to was that men were preferred candidates.

Responsible use of AI

There is a great deal to be positive about when it comes to AI. Any emerging technology that has the power to disrupt the existing structures of individuals and organisations must be assessed for its potential risks.

But being mindful of the downsides does not mean becoming blinkered to the benefits. Indeed, decision-makers have been warned against doing just this, or else risk losing out on the clear improvements that careful use of AI can bring.

"Look at how you are using technology today during critical interactions with customers - business moments - and consider how the value of those moments could be increased. Then apply AI to those points for additional business value," said Whit Andrews, distinguished vice president analyst at Gartner.

"AI projects face unique obstacles due to their scope and popularity, misperceptions about their value, the nature of the data they touch, and cultural concerns. To surmount these hurdles, CIOs should set realistic expectations, identify suitable use cases and create new organisational structures."

Gartner advises that business and IT leaders should endeavour to cut the AI hype away from reality by carefully considering and weighing up the opportunities vs risks. Obsessively focusing on automation, rather than the bigger picture, will only obscure the wider benefits, the analyst firm warns.

In July 2022, the UK government and Alan Turing Institute jointly announced the establishment of the Defence Centre for AI Research (DCAR). Its goal is to develop areas of AI research that are currently proving challenging to implement, such as training without the need for large data sets, AI ethics, and war gaming. 

"Everything we love about civilisation is a product of intelligence," said Max Tegmark, president of the Future of Life Institute.

"Amplifying our human intelligence with artificial intelligence has the potential of helping civilisation flourish like never before as long as we manage to keep the technology beneficial."

Organisations can also check if their use of AI systems breaches data protection laws using a risk assessment toolkit launched by The Information Commissioner's Office (ICO). The AI and Data Protection Risk Assessment Toolkit, available in beta, draws upon the regulator's previously published guidance on AI, as well as other publications provided by the Alan Turing Institute.

It contains risk statements that organisations can use while processing personal data to understand the implications this can have for the rights of individuals. Based on an auditing framework developed by the ICO’s internal assurance and investigation teams, the toolkit also provides suggestions for best practices that companies can put in place to manage and mitigate risks. 

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