Lots of examples of AI applications can be found in our day-to-day routines. Many of them are making things easier, such as maps alerting us to roadworks ahead, or chatbots addressing our customer service issues. But what about AI tools being used in a professional setting, like application scanning and facial recognition? Assemble You Limited emphasises that for those, it’s important to consider the good and the bad. Basically, it’s essential to recognise that bias exists within these technologies and that they reflect and perpetuate discrimination.
1. The mechanics of AI bias and discrimination
It might be surprising to hear that artificial intelligence can be biased. It is a digital tool, so how can it be? Here, a distinction needs to be made between biases that exist within technologies themselves, and biases that exist in the system in which the technology is being developed.
AI systems are trained on vast datasets, often collected from the real world. This data can sometimes contain biases or unfairness from human decisions or historical inequalities - even if we remove sensitive details like gender, race, or sexual orientation. If historical hiring data exhibits gender bias, an AI used for recruiting may inadvertently learn and perpetuate this bias by favouring one gender over others.
Let’s explore some of Assemble You Limited’s practical tips and advice on addressing these AI biases and discrimination.
2. Awareness is key
Recognise that AI systems can unintentionally perpetuate bias. Don’t just accept the results delivered via AI systems. Instead, be vigilant in questioning the fairness of AI-driven decisions.
3. Diverse data matters
Leaders must advocate that any AI powered tool used within their organisation be trained using diverse and representative data to counteract inherent biases. Insist on data sets that include different races, genders, backgrounds, disabilities, and perspectives.
4. Algorithm Transparency
Seek transparency in AI algorithms. Understand how decisions are made and what factors are considered. Companies should provide explanations for AI driven decisions.
5. Ethical AI frameworks
Encourage your organisation to adopt policies outlining ethical AI frameworks and guidelines that prioritise fairness and inclusivity.
6. Bias impact assessment
Conduct a bias impact assessment before deploying AI systems. Understand how the systems’ decisions may affect different groups and make necessary adjustments. User feedback encourages users to provide feedback on AI driven experiences. Their input can be invaluable in identifying and mitigating biases.
It’s inevitable that AI will be used to perform more and more functions across organisations. Therefore, Assemble You Limited believes it’s up to all of us to look for, recognise, and seek to reduce and eliminate biases across our workplaces. Advocate for diverse training, data support, transparency and ethical AI frameworks, and continuously monitor and fine-tune AI algorithms. By taking these actions, we can all look forward to a fairer, AI-powered future.
If you want to hear more of Assemble You Limited on this topic, listen to Avoid Bias and Discrimination when using AI.
