Artificial Intelligence (AI) can improve Diversity, Equity, and Inclusion (DEI) efforts in workplaces by detecting biases, improving hiring and performance management, and identifying patterns of discrimination. However, AI can also perpetuate existing biases and discriminate against underrepresented groups if not carefully developed, monitored, and tested for inclusivity. Companies must regularly audit algorithms to ensure they are free from discriminatory elements and have trained individuals to review AI outputs and intervene when necessary. To ensure responsible and ethical AI innovation that supports DEI efforts, diverse and representative data sets, transparent AI systems, and clear ethical guidelines are essential.
Artificial intelligence (AI) has the potential to revolutionize almost every industry. It also poses significant risks to society and humanity, which is why it is crucial to have robust guidance and resources from both the public and private sectors to ensure its positive impact. Along those lines, the Biden-Harris administration recently released a fact sheet about their efforts to safeguard people’s rights and safety while maximizing the benefits of this groundbreaking technology.
One area where AI can either bolster or undermine progress is in corporate Diversity, Equity, and Inclusion (DEI) initiatives. AI can be used to further workplace DEI efforts, such as improvements to hiring and performance management processes, bias detection in content, and identifying patterns of discrimination. However, AI can also perpetuate existing biases and is only as good as the data that it is trained on. Therefore, it is important to ensure that AI is helping rather than harming DEI efforts.
There are several ways in which AI can be used to further workplace DEI efforts. AI algorithms can flag biases and improve hiring, performance management, and compensation policies, ensuring equal opportunities for employee growth. AI recruiting tools can help companies balance the pool of candidates by improving the inclusivity of the language used in job descriptions and sourcing candidates from underrepresented groups. AI for employee engagement can help a company surface when underrepresented groups feel disengaged, unearth root causes, and launch targeted interventions and support programs to improve retention and advancement among a diverse range of employees.
AI models can play a crucial role in promoting diversity and equity at all stages of the employee journey. By replacing quantitative questionnaires with a more nuanced analysis of employees’ qualitative feedback, companies can gain a deeper understanding of their employees and identify patterns of discrimination. Also, a properly trained AI can understand individuals more deeply and comprehensively than managers. AI can precisely comprehend the context and problems of each person, take into account specific parameters, and make decisions that surpass the limitations of managers.
While AI can help promote DEI, there are risks involved if it is not properly designed and implemented. Existing patterns of bias and discrimination that lurk in the workplace also lurk in the data. Without DEI-conscious development, AI will pick up these patterns and return outputs that can perpetuate and even exacerbate biases. AI systems should be carefully developed, monitored, and tested for fairness, explainability, and inclusivity to mitigate these risks.
It is important to understand what data was used to train the AI and if the creators considered how bias in the data could impact the outcomes. When you use AI to have full control and make decisions, not just augment or help a manual process, and when folks don’t fully understand how the AI is making that decision, it can perpetuate and amplify bias.
It’s also important to recognize that AI cannot replace trained DEI practitioners; it can only be used to intentionally scale their expertise. DEI is based on human experiences, which means companies cannot let the convenience of AI override the human element when making equity decisions.
To ensure that AI is helping rather than harming DEI efforts, companies should regularly audit algorithms to ensure they are free from discriminatory elements and take measures to secure and protect the data collected and used for AI systems. Companies should also have a trained human in the loop to review AI outputs and intervene when necessary.
To ensure responsible and ethical AI innovation that supports DEI efforts, companies must adopt safeguards such as diverse and representative data sets, regular audits, transparent AI systems, and clear ethical guidelines.
As policymakers work on developing rules around AI, people-first organizations need to come together and create guidelines to ensure ethical and equitable use of the technology.
