Industry Change: Turning Exclusive Events into Entry Points for Diverse Talent and Disruptive Recruitment Solutions

Table of Contents

• Making AI Events More Accessible
• Who Benefits From AI in Diverse Talent and Disruptive Recruitment Solutions
• Who Do AI Careers Appeal To?
• Recommendations
• References

Making AI Events More Accessible

Artificial intelligence (AI) has become a key focus area for global dialogue. Indeed, conferences, conventions, and other events worldwide bring together industry leaders, entrepreneurs, investors, and developers. They accelerate collaboration in AI through these platforms and, ultimately, the rate at which products and services are designed, produced, distributed, or in Diverse Talent and Disruptive Recruitment Solutions otherwise entered into public space. Moreover, the people who create and advance this technology come from many different sectors, disciplines, and geographies.

This type of environment is full of possibilities. For those looking for new clients, customers, or careers, it is particularly beneficial, because new connections are established, and these connections expand social and professional networks. However, there are many stakeholder groups that remain unaware of these events, in part because outreach activities and announcements are not allocated for their communities. This lack of accessibility makes these events appear more exclusive than they could or should be and adds complexity to the multitude of challenges that narrow the benefits of AI and the populations that find AI careers appealing.

In fact, we should determine the value of industry events based on these factors. Indeed, these factors are crucial for anyone looking to make AI data more inclusive and ensure success in the data economy.

Who Benefits From AI in Diverse Talent and Disruptive Recruitment Solutions

Conferences, industry events, and conventions provide opportunities for AI experts to share information, persuade, and coalesce. Representatives from government and regulatory agencies may attend these events or review proceedings. However, the dialogue is centered on the specialized knowledge of relatively few individuals, which reduces avenues for others to be heard.

This is alarming because there are approximately 2.6 billion people without access to the internet, and those with the least access are from the least ‘developed’ countries. They are often separated from discussions that explore the ways AI impacts their lives and mechanisms of transparency or accountability for any negative impact. Further, people who live in conflict-affected areas are frequently separated from AI benefits. For instance, 1.6 billion people have been left with no access to basic health services. As a consequence, they do not enjoy the diagnostic tools, medical devices, recommendations for treatment, and other services powered by AI.

In addition, women comprise only about 22% of AI professionals worldwide. Thus, even if they live in a developed country, they are most often afforded a consumer or user position. This position is disconnected from AI expertise and likely counterintuitive to event hosts looking to invite leaders and authorities. Therefore, consumers are situated to disseminate information to one another at the post-production stage, with less accolades or potential for visibility.

As a result, the experts attending and hosting these events do not represent all communities. The data they use to train AI doesn’t either. Furthermore, the problems AI experts claim to resolve are a reflection of value creation in geographies with concentrated wealth, a narrow view of inclusion for AI data, and an echelon in the data economy, where insiders have amassed concentrated digital power. In this context, it is more challenging to make AI inclusive.

Indeed, the main objective of industry partnerships and networks is to commercialize AI. It is not to solve human rights violations, remediate the many facets of the digital divide, or increase diversity in AI through a disruptive recruitment solution. These latter objectives could be fulfilled if we question more deeply what AI should be doing, where it should be applied, and who it should benefit.

Everyone should have a chance to explore these questions and propose answers. Thus, increasing AI engagement among diversity strategists, consumer advocates, and women in leadership is critical. In addition, engagement from workforce development strategists, including career advisors, training providers, and adult learning specialists is particularly important. These experts have the capacity to make careers in technology more relevant and accessible to underrepresented communities. 

For instance, they can act as intermediaries, introducing minority entrepreneurs, industry associations, mentors, executives, and other success models to jobseekers who might not consider a career in technology otherwise. Conceivably, when AI careers become attached to a career pipeline, minority voices can be elevated from within the industry. From this vantage point, proximity to AI training models can be leveraged to make the data AI systems generate more inclusive.

The trajectory outlined here is important to underscore because it is more difficult to make change on the periphery. Therefore, conferences, industry events, and conventions should be recognized as entry points to further connections between workforce stakeholders, investors, employers, and executives in the technology sector. Through these connections, narrow conceptualizations of diversity can be countered as partnerships are formed to solve recruitment gaps and increase business revenue and growth.

Who Do AI Careers Appeal To?

Demand for talent with technology skills is increasing. Yet, women and minorities remain underrepresented in the technology sector, where fewer leadership roles, training opportunities, professional networks, and career pathways can limit AI’s appeal. Workforce Development Boards (WDBs) are among the stakeholders best suited to tackle this problem. For instance, WDBs receive federal funding to organize recruitment and training programs.

In addition, WDBs have demonstrated success in the recruitment and placement of women, minorities, and jobseekers of all ages into career pipelines in the technology sector. In fact, they provide no-cost, second-chance, and accelerated education for trainees who have been justice-involved, laid off from work, separated from school, or constrained by low-income jobs. Thus, WDBs have the capacity to leverage an existing career pipeline to help industry leaders access talent and increase diversity in AI. Moreover, the attributes of partnerships between WDBs, industry leaders, and investors are important to underscore. For example, federal funding for the recruitment and training WDBs undertake reduces costs for employers.

Furthermore, AI data can help career advisors and training providers produce customized, differentiated learning experiences. In fact, AI could synthesize trainee profiles and other information to inform recommendations for courses, materials, activities, and careers best suited to jobseekers. This is particularly important because, with AI data, WDBs can better demonstrate coherence between the aspirations of jobseekers and the training programs and employers they are connected to.

Federal donors could leverage these results to share best practices across the workforce and other programs where they want to leverage AI in public services to improve quality, efficiency, and impact. Thus, the more opportunities workforce stakeholders have to attend industry events and partner with AI investors and leaders, the more they can place jobseekers into AI careers, where their diverse backgrounds and skills could address business objectives and make AI more inclusive at the same time.

Recommendations

We should not continue hoping AI will solve the world’s challenges while many of us work in isolation or collaborate as though commercial use is the only AI benefit worth exploring when we are convened. We must also resist settings that are constructed to be exclusive and minimize partnership opportunities.

The road to inclusive AI data begins with greater interest in AI careers among women, minorities, and other underrepresented groups. The career pipelines, success models, and leadership training they have access to could make AI careers seem more attainable and foster engagement that will solve unmet needs for talent in the technology workforce. Diversity recruitment is therefore a solution, and WDBs are critical to this process.

Thus, one of the most practical ways to make AI inclusive is to ensure leaders in the workforce, diversity, and technology sectors are connected. Conferences, industry events, and conventions are frequently held around the world and should be recognized as open doors where these connections can be made.

WDBs should readily deploy representatives to AI events with a view to partnership engagement, and event hosts should ensure diverse attendance through outreach activities. Diversity in AI data can be achieved through these activities. In fact, we should ensure there are platforms for inclusive partnerships in AI and other forms of machine learning, even if we are not among the experts in the technology space. 

For a broader discussion about the intersection of workforce development boards, diversity and inclusive partnerships, we welcome you to read our related articles and comment below. 

References

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Nicolaci Da Costa, P. (2019, March). Tech talent scramble. International Monetary Fund. https://www.imf.org/en/Publications/fandd/issues/2019/03/global-competition-for-technology-workers-costa

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United Nations Children’s Emergency Fund. (2020, December 1). Two-thirds of the world’s school-age children have no internet access at home, UNICEF+ITU report says. https://www.unicef.org/turkiye/en/press-releases/two-thirds-worlds-school-age-children-have-no-internet-access-home-new-unicef-itu

United Nations Development Programme and Mohammed Bin Rashid Al Maktoum Knowledge Foundation. (2022). Future of knowledge: A foresight report – Leveraging Transformative capacities to meet future risks. Retrieved March, 22 2024, from https://www.undp.org/publications/future-knowledge-foresight-report-leveraging-transformative-capacities-meet-future-risks

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