Marla MacInnis, Bachelor of Commerce student and CoBS 2023 student CSR competition Winner at Smith School of Business, probes the question of diversity and inclusion in firms, why it pays to do so, and how AI can boost an organization’s capacity to walk the talk of its DEI policy.  

The Illusion of Inclusion: How Artificial Intelligence can challenge the ‘business case’ for diversity by Marla MacInnes.

Orchard mason bees are efficient pollinators of fruit trees. Bumblebees, however, are larger in size, with tongues that enable them to reach nectar deep within flowering plants. Both are important pollinators, yet each possesses unique characteristics better suited to certain plant species. It is this functional diversity which helps maintain the overall health and resilience of the ecosystem.

Within the realm of biology, functional diversity is not a new concept. In fact, the Greek Theophrastus likely identified the idea of functional diversity as early as 300 B.C. Since then, various studies have illustrated the resiliency that results from functionally rich ecosystems. So, why have we yet to extend this understanding to humans in an organizational context? Why are businesses just now beginning to fully appreciate the power of diverse workforces?

The “inclusion chasm”

In 2020, the murder of George Floyd catalyzed a social reckoning in North America. Many individuals sought to better understand the racial inequities and injustices that have long since plagued our history. The COVID-19 Pandemic further magnified these disparities, motivating many consumers and employees to advocate for reform. Among the primary targets? Corporate America.

There is no doubt that progress has been made. In recent years, we’ve witnessed many organizations investing heavily in diversity initiatives, as there is an understanding that heterogeneous, diverse workforces yield greater innovation and increased performance. Accordingly, at most large and multinational companies, diversity and inclusion have become organizational imperatives.

However, a huge gap remains between what organizations are saying and what they are doing to promote inclusion. There remains a glaring racial divide in the upper echelons of the business world and slow progress with regard to racial and gender representation. I’m calling this gap the “inclusion chasm,” and proposing that it is largely the result of organizations exclusively focussing on the business case for diversity.

Moving from shareholder value to shared value

The business case implies that there must be economic grounds to warrant the pursuit of diversity. In short, this is disconcerting – why must businesses require economic rationale to justify treating humans with equity and compassion?

The case for diversity should not be restricted to its business value or functionality. An organization’s approach to diversity, equity, and inclusion (DEI) should not be solely valued for its propensity to maximize revenue and profits. Yes, research shows that diverse companies are 36% more profitable (1), 87% better at making decisions (2), and 19% generating higher innovation revenues (3). However, businesses shouldn’t require heaps of statistics to justify their DEI initiatives. They should prioritize diversity and inclusion because it is the moral thing to do – not because it is the most lucrative. With this, I challenge organizations to shift their line of questioning. Ask not: “What is the most economical thing to do?” but “What is the right thing to do?”

This shift in questioning is reflective of a shift in mindset – organizations must move beyond the business case of diversity and towards a moral one. It is no longer enough for organizations to assume a performative, surface-level approach by simply hiring individuals from diverse backgrounds. They cannot just ‘add diversity and stir.’ Rather, they must consciously work towards closing the inclusion chasm by prioritizing shared value, not shareholder value. To do so, I propose an innovative method: artificial intelligence.

Introducing artificial intelligence to the organizational ecosystem

It is impossible to dispute the advent of AI. Artificial intelligence is permeating all aspects of modern-day society, and the business landscape is no different. Since 2017, AI adoption has more than doubled, with 50% of firms using AI in some capacity (4). Unquestionably, artificial intelligence has become an integral part of an organization’s strategy, and since achieving racial equity is one of the most important imperatives companies are faced with, AI must be integrated accordingly. This being said, it is necessary to acknowledge the contradictory nature of this proposition. I’m encouraging businesses to put people at the centre of their organizations. Yet, I’m proposing artificial intelligence – a form of technology rather removed from the human experience. The irony is salient. However, given the rapid industrialization of AI, businesses have no choice but to navigate such a paradox. At the risk of being out-competed, organizations must learn to leverage AI capabilities while simultaneously maintaining a human-centred approach. Reconciling such a contradiction gives rise to a vital question: “How can businesses use AI to maximize the human potential of everyone in the workplace?”

The “A” stands for accountability

In the midst of such tumultuous economic and social times, neither consumers nor employees are content with vague platitudes for change. Organizations must hold themselves accountable for their diversity and inclusion initiatives by developing clear and robust measures to track their diversity and inclusion efforts. And while designing these inclusion metrics may be an art, measuring them is most definitely a science. Luckily, artificial intelligence offers a bias-free method of gaining such targeted and meaningful DEI data.

With the help of AI algorithms, organizations can measure disparities in pay and promotion rates, determine the diverse composition of leadership teams, compare retention rates, and analyze differences in career trajectories. Armed with this information, organizations can identify risk areas, prioritize initiatives, reallocate resources, and uncover “blind spots” that may be otherwise hidden from leadership teams. Then they can make the necessary adaptions, refining and tailoring their DEI approach accordingly. In the context of diversity and inclusion, “what gets measured gets done.” And with AI-generated data, organizations have the chance to remove any emotionality and subjectivity. This allows them to consider their DEI position objectively and rationally – you simply cannot argue with cold, hard facts. With this, organizations are forced to confront how they are performing relative to their inclusion objectives. Facing this reality head-on brings organizations one step closer to narrowing the inclusion chasm.

The “I” stands for inclusion…

Increasing the overall representation of BIPOC employees is often the first step of any DEI strategy. But what is, arguably, more problematic than underrepresentation is the lived experiences of BIPOC employees. People belonging to underrepresented groups continue to face explicit and implicit forms of racism within organizations. This can manifest as “modern racism” (when people believe that BIPOC no longer face discrimination), “aversive racism” (when people change their behaviour around BIPOC – or avoid them altogether) and “microaggressions” (when people intentionally or unintentionally express a prejudiced slight). In short, diversity does not precipitate inclusion. And so, while achieving a diverse organization is hard, achieving one that is inclusive is even harder. But what if AI could be used as an inclusion diagnostic?

We’ve already discussed relying on AI-generated data to monitor DEI metrics. However, it is possible that artificial intelligence can provide further insight into an organization’s working environment by measuring the objective level of “inclusion.” To do this, AI can monitor internal working conditions and organizational culture, ultimately determining whether day-to-day operations are anti-racist. For example, natural language processing algorithms can detect disparities in how BIPOC employees are addressed, as well as identify offensive language and microaggressions. Further, analyzing email metadata can reveal discrepancies in latency time and access to social networks. This will help organizations identify any hidden biases or covert forms of racism that may be hindering their DEI strategy. Without AI, this would be nearly impossible to detect.

…and insight

I encourage business leaders to ask themselves a single question: Do you understand the BIPOC experience within your organization?

Approximately 75% of employees in underrepresented groups do not feel they’ve personally benefitted from their companies’ diversity and inclusion initiatives (5). This reveals a severe misalignment between leadership and employee experience. Somewhere along the way, organizations’ DEI initiatives are failing to deliver value to those they are intended to support. To address this disconnect, I, once again, propose artificial intelligence.

Beyond quantitative data and metrics, employee anecdotes provide a valuable way to gain insight into an organization’s DEI strategy. Using sentiment analysis solutions, AI can capture employee feedback, perspectives, and moods, further segmenting this information to understand the perspectives of certain groups. This acknowledges the fact that BIPOC employees experience unique race-based stressors that are often unacknowledged in predominantly white organizations.

Further, the anonymous, automated element of AI allows employees to document their perspectives and lived experiences more honestly, without fear of retribution. This fosters a psychologically safe environment that acknowledges and welcomes feedback from all employees. Feeling genuinely valued, empowered, and respected involves more than just feeling included – it means having your needs, interests, and concerns taken into account. True organizational inclusion stems from this understanding that every employee matters, and capturing employee perspectives with AI is one way organizations can foster this sense of worth. The intended result is an organizational culture that prioritizes humanity.

Simply part of the larger ecosystem

To be clear, I am not suggesting that companies outsource their diversity and inclusion strategies to AI. Nor am I suggesting that systemic and organizational racism can be solved by a pattern of 0s and 1s. What I am suggesting is that, when accompanied by inclusive leadership, strong ethics, and a racially just corporate culture, AI can be an effective way to support a strong and pervasive DEI strategy.

Artificial intelligence doesn’t excuse organizations from doing the actual work. The process is only effective when accompanied by committed, dedicated, and relentless staff who engage with it. AI simply holds them accountable. It measures inclusion. It shows impact. This is how organizations can move beyond the diversity case and towards a moral one that is characterized by reparations and restitution.

The difference between humans and bees

Now, I encourage readers to re-visit my initial question: Why are businesses just now beginning to fully appreciate the power of diverse workforces? It is because we consider ourselves fundamentally different from other biological species – and rightfully so. There’s a reason we do not operate the same as orchard mason bees: We are human, and we have the capacity to think, to feel, and to morally reason. To treat others with dignity and respect. But we also

have the fallibility of succumbing to prejudice and perpetuating discrimination. This is the human condition.

And yet, despite these differences, it might be time to take a lesson from the orchard mason bees. It is time for organizations to fully embrace the functional diversity that contributes to such powerful, rich ecosystems. Now, more than ever, organizations must strive to benefit from the diverse experiences, knowledge, and skills of all people – not a select few. The path toward these racially-just workplaces will not be easy; it will be hard and uncomfortable. But it begins with a single commitment: if the price of economic success is equity, the cost is too much.

References:

• 1) Sundiatu Dixon-Fyle et al. “Diversity wins: How inclusion matters,” McKinsey & Company, May 19, 2020, https://www.mckinsey.com/featured-insights/diversity-and-inclusion/diversity-wins-how-inclusion-matters.
• 2) Erik Larson, “New Research: Diversity + Inclusion = Better Decision Making At Work,” Forbes, September 21, 2017, https://www.forbes.com./sites/eriklarson/2017/09/21/new-research-diversity-inclusion-better-decision-making-at-work/?sh=4da5575b372d.  
• 3) Rocio Lorenzo and Martin Reeves, “How and Where Diversity Drives Financial Performance,” Harvard Business Review, January 30, 2018, https://hbr.org/2018/01/how-and-where-diversity-drives-financial-performance.
• 4) McKinsey & Company, “The state of AI in 2022 – and a half decade in review ,” McKinsey & Company, December 6, 2022, https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review.
• 5) Matt Krentz, “Survey: What Diversity and Inclusion Policies Do Employees Actually Want?” Harvard Business Review, February 5, 2019, https://hbr.org/2019/02/survey-what-diversity-and-inclusion-policies-do-employees-actually-want.

Useful links:

• Link up with Marla MacInnis on LinkedIn
• Read a related article: The Family of beings: People, animals and diversities
• Discover Smith School of Business, Queen’s University, Canada
• Apply for the Smith Bachelor of Commerce.

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