AI is rarely far from the headlines these days. From allegations of Deepseek plagiarising OpenAI data, to several countries banning the former from government devices, its development and implementation can seem shrouded in debate. But even as these controversies rage, the UK government has announced the application of AI in a breast screening trial and it was recently used to decipher a manuscript that was badly scorched in Herculaneum, enabling it to be read for the first time in 2,000 years. The issue, clearly, is not with the technology itself, but with how it is used. Here we examine how transparency and trust can be built into AI systems to enable a more ethical approach to its use.
People mistrust what they don’t understand so to break down any mistrust or even distrust of AI, they first have to understand what it is and how it can play a vital role in enhancing their lives – whether that’s in the workplace or at home. In the workplace this understanding can be enhanced for employees, stakeholders, and customers by considering the ethics of its use, whatever its application. The challenges of implementing and upholding ethics within AI can be broken down into three main considerations:
Employees, stakeholders, and customers all need to trust an organisation’s AI systems, whether they’re talking to a chatbot about a product or service, or using it to inform recruitment decisions. Therefore, it’s important that leaders implement AI strategies that promote trust throughout an organisation.
Organisations can mitigate bias by training their AI models to use data that is both representative and diverse – this means using data that includes a wide range of information from people of different demographics. The data sources and algorithms should be continually monitored to ensure it’s up-to-date, and any discriminatory patterns or biases that have occurred should be corrected. It’s also important that leaders communicate how they’re preventing and addressing bias to ensure fairness and transparency.
Data that’s used to train AI models should be anonymised to comply with regulations, and it should be safeguarded throughout its use to ensure sensitive information, such as personal details (especially in the case of financial institutions or healthcare providers), is stored securely. Strict data governance protocols should be adhered to and advanced encryption methods deployed.
Leaders must encourage a culture of ethical responsibility around every aspect of the development of AI systems and their deployment, and communicate their decisions in clear policies. In addition, all employees within an organisation should be given regular training so that they understand the importance of the highest standards of the ethical use of AI.
AI offers unlimited possibilities for organisations across all sectors to drive efficient and effective business practices forward, enhancing results, saving time, and cutting costs. However, its use must be tempered within an ethical framework to ensure that transparency and trust are built into its use.
For expert advice on any of the topics discussed in this blog, contact Brighter Consultancy.