Generative Artificial Intelligence (Gen AI) dominated the global conversation in 2023. Most organisations are optimistic and brainstorming ways to integrate AI into their businesses. Let us begin 2024 by reflecting on gaps in diversity so that we can understand and finetune design. How inclusive is the data that AI is using from the internet to train itself? How diverse are the teams working on the technology and onboarding these solutions into our businesses? If you are leading digital transformation in your organisation, you will be considering these questions.
In 2023, Forbes reported that women hold less than 26.2% jobs in tech companies with more than 10,000 employees globally. A recent report by AIM Research, ‘Women in Tech 2023 (India)’ has some interesting findings on diversity in tech organisations.
Gender metric is relatively easier to showcase. What about sexual orientation, disability, social mobility, and other dimensions of diversity that may not be immediately noticeable? These questions apply not only to tech but also AI, Gen AI and other industries. Do AI teams only need advanced technical degree holders? What about non-technical, less advanced professionals with a passionate, creative outlook? AI needs to analyse and present the data in a business context, so team leaders need well-rounded teams to be effective.
Gaps in Hiring and Talent Retention
This blog focuses on the diversity of teams that are working on AI solutions. In law firms, we need to consider the following questions:
Biases while shortlisting resumes – With law firms looking to ramp up teams to integrate AI, we need to acknowledge biases that exist in our recruitment processes. For instance, some would say that there are not enough applications from diverse candidates, others say that processes are inherently or unconsciously biased. By acknowledging these biases, we will be able to look for solutions that the situation needs.
Biases while interviewing – Should Gen AI teams have its own version of ‘blind auditions for orchestras’ as adopted in the United States in the 1970s to address racial and gender disparity? Instead of interviews, would a pure quality-based assessment lead to a more diverse team?
Gaps in performance – What happens when the diverse team member who has been recruited after a lot of effort fails to pull their weight? Should organisations provide more leeway for underperformers only because the team member is ‘diverse’? Would other ‘non-diverse’ team members feel less ‘included’?
Getting it Right
Building an equitable team and workplace is hard. Especially in law firms where the primary focus is on practicing lawyers. Gen AI could be the answer that this situation needs. Algorithms helping to measure productivity and making hiring, promotion and training decisions could be a game changer for any business and its employees.
Incorporating AI in team building
Identify goals: If improving recruitment is the goal, AI could help identify skill gaps, accelerate selection process, and reduce time to hire.
Embrace the data driven mindset: To leverage good data, teams need to develop basic rules for data collection. Successful analyses will require consistent and structured data.
Strong translation: Organisations need skilled communicators who can use data analytics to interpret insights, engage stakeholders and influence business changes.
Organisations can harness the power of Gen AI to build efficient and equitable workplaces by asking the right questions when training the AI and people analytics tools, having strong bias monitoring, and spotting blind spots that may arise due to a less diverse team.
The opinions and views expressed in this content belong solely to the author(s).
