Building an inclusive future with AI
The invisible force that powers many technologies we interact with everyday — Artificial Intelligence (AI), is not just algorithms and complex coding but the foundation of the system and processes that guide our daily conversations and experiences. A soaring trend in the world of tech, AI is the present and future of human interactions.
As per our latest Future of Skills report, AI is one of the fastest rising skills in APAC. However this sector misses out on something crucial – a gender balanced workforce. Today in the APAC region only 2 out of every 10 AI professionals are women. This trend is consistent across the different countries in our region.
Building an inclusive technology
The AI workforce of today is building the technology of tomorrow and the norms that will guide the future of AI. This technology has already started touching various spheres of business and consumers alike. Different industries like education, healthcare, retail, finance and manufacturing are discovering applications of AI for their businesses. This impact is going to continue to grow and penetrate further. As AI touches more and more people, it is important that we develop it with inclusivity in mind and it does not create unconscious bias for the users of the technology. This starts with having diversity in the teams developing AI. Tech that is built from the perspective of both genders will be more inclusive and a representation of the real world.
What does this mean for your business?
While organisations around the world are prioritizing gender diversity initiatives, putting special emphasis on the AI talent pool becomes even more crucial as the gender gap is much more stark in this talent pool than the rest of the base— following the trend that we see in STEM* talent. A one-size-fits-all strategy may not work for this talent pool considering the supply and availability of skilled talent in this field is sparse.
*Science Technology Engineering Mathematics
Gender balance in this talent pool for tech companies is a no-brainer as they look to build capabilities and solutions in this field. For other industries beyond tech, even though they may or not need AI skilled talent in-house, but they will be buying solutions from tech companies that will influence the work and decisions of their workforce. Hence, gender diversity in the decision-makers & influencer segments will become important.
3 things you can start thinking about
Understand your current gender split and goals
You can start by benchmarking your company’s current gender split in this talent pool against competition and industry. Once you have the baseline, you can start setting aspirational recruiting and upskilling goals. You can get this started through LinkedIn’s self- serve analytics tool LinkedIn Talent Insights.
Strengthen employer brand to appeal to diverse audiences
Make sure that your employer brand shows up with a diverse voice, tone and look. Highlighting stories of women leaders in the AI field can help attract top female talent. Using sponsored content, you can reach out to the AI talent pools and help engage women who may not be aware of your brand.
Invest in your existing workforce
Can a software engineer or data scientist in your company be upskilled to build skills and capabilities in AI? Building career pathways for existing women employees with the relevant foundational skills and interest can help build niche talent from within the company while closing the gender gap.
Behavioural insights for this report were generated from the billions of data points created by more than 645 million members in over 200 countries on LinkedIn today. We have inferred the gender of members included in this analysis by classifying their first names as either male or female or by pronouns used on their LinkedIn profiles. Members who gender could not be identified as either male or female were excluded from this analysis. This analysis only includes members located in countries where we could infer gender for at least 67% of the member base.
Gender identity isn’t binary and we recognise that some LinkedIn members identify beyond the traditional gender constructs of “male” and “female”. However, LinkedIn gender data inferred on the basis of first name and pronouns both use the implied, and currently does not account for other gender identities. As members begin to self-report gender, we will be able to share more inclusive gender data.