Artificial intelligence (AI) has been all over the news recently, attracting widely varied responses. On the positive side, AI has huge potential to make aspects of social and working life easier and more efficient. The large language model (LLM) that AI apps use to search for information and convert it instantly to text according to your specifications can be incredibly useful, especially for small businesses.

But it is also important to understand the potential for false information when using these apps, especially in fields like law, politics and education. There is also a chance that AI can have negative consequences in fields where misattribution, misinformation and plagiarism are an issue, like academia and the media.
 

What exactly is AI?

The idea of AI goes back to the ‘father of computer science’, Alan Turing. In his groundbreaking paper Computing Machinery and Intelligence in 1950, Turing asked, ‘Can machines think?’ The test to find out, in which a human interrogator tries to distinguish between a computer and human text response, is still called the Turing Test. No machine has passed the test yet, but current versions of AI might be steps along the way.

The simplest definition of AI is that it’s a technology that combines computer science and large datasets to enable problem-solving. The current hype around AI comes from the release of OpenAI’s ChatGPT, which is a huge leap forward in natural language processing, where the programme generates various types of texts according to the user’s instructions.

But this type of AI can also learn the grammar of software code, molecules, natural images, and a variety of other data types. As the hype around the use of AI in business takes off, conversations around ethics become critically important.

Some of the main ethical issues raised by AI are:

• AI’s impact on jobs This has become a burning question as industries seek to replace many text- and writing-based jobs (in education, law and media, for example) with instantly generated AI texts. AI automation and robotics could render millions of jobs in these and other fields obsolete.
  
  
• Privacy This is often discussed in the context of data security and hacking, but the rise of AI does present additional complexity to the protection of personal and business data security.
  
  
• Bias and discrimination Because LLM ‘teaches’ AI using existing texts authored by humans, it presents several ethical dangers regarding bias and discrimination, from racial and gender profiling in HR roles, to issues around facial recognition technology and social media algorithms. Several companies have suspended development of facial recognition software, citing such concerns.
  
  
• Accountability There is currently no legislation to regulate the use of AI, so there is no incentive to develop ethical systems, except for the impact on profits if AI were to prove damaging to a business’s operations or reputation.
   

Common AI apps for your business

• Speech recognition Also known as automatic speech recognition, computer speech recognition, or speech-to-text, this uses natural language processing to process human speech into a written format. Many mobile devices incorporate speech recognition into their systems to conduct voice searches or to make texting easier. 
  
  
• Customer service It’s commonplace now to encounter virtual agents – usually AI chatbots – on the customer journey. They tackle frequently asked questions around topics like shipping, provide personalised advice, cross-sell products or even suggest sizes for online shoppers. AI is changing the way we think about customer engagement across websites and social media platforms.
  
  
• Recommendation engines This well-embedded AI technology uses consumer data from past purchases to discover data trends that can be used to develop more effective cross-selling strategies.
  
  
• Automated stock trading Designed to optimise stock portfolios, AI-driven high-frequency trading platforms make thousands or even millions of trades per day without human intervention.
   

Of course, these are all examples of AI already at work, helping various businesses and sectors very successfully. The current wave of text-based generative AI technology also has various potential applications across sectors like education (generating essays and other written responses), the legal profession (generating case notes or finding case precedents) and many business requirements for pro-forms or even more interpretive textual responses as part of a task – activity reports, for example.

Risks and challenges for your business

As with any powerful new technology that can aid efficiency in any size business, there are risks associated with AI. These include:

• Human interactivity and safety Despite the human-designed parameters of most AI technology, there have already been cases where the technology – especially AI chatbots – begin communicating directly with each other in a way humans do not yet understand. This rapid machine learning can lead to all kinds of data disruption and security breaches.
  
  
• Trust Many humans who will use and interact with AI technology don’t fully understand how it works, nor is it easy for business owners to trust tech systems that are designed to learn by themselves and don’t have a centralised method of control or regulation.
  
  
• Job losses The World Economic Forum estimates that AI has already cost more than 70 million jobs, mostly the kind of repetitive clerical work that can be done more cost-effectively by technology. Ideally, businesses adopting AI should invest in upskilling and reskilling their human workforce in different areas, including managing and regulating AI systems. Rather than replacing jobs, companies can also use AI to augment the services and capacity of employees and make them more productive.

As with any such technological advance, the AI apps currently ‘exploding on the scene’ have in fact been in use behind the scenes for some time. While change is often challenging, businesses that can overcome the pitfalls of AI can use the technology for more cost-effective and efficient systems in their day-to-day functions. This applies to businesses of any size, but AI could be of particular benefit to small and medium enterprises working with very tight margins.