In today’s business landscape, the value of a diverse workforce has become indisputable. Hard numbers support its positive impact on businesses’ top and bottom lines. A recent survey revealed that 62% of participating executives rated diversity and inclusion as a high or top priority. Diverse organizations are often more successful than others.
For example, McKinsey & Company found that gender-diverse organization are 15% more likely to outperform their peers, while ethnically-diverse organizations are 34% more likely to do so. With many of the world’s leading economies facing an increasingly aging population, it is encouraging to see that retaining older workers can increase business productivity. A PWC study of the 36 countries that are part of the Organization for Economic Co-operation and Development (OECD) determined that boosting the employment rate of older workers could add $2.6 trillion to the GDP of these nations.
Despite recognizing the importance of diversity and making considerable investments in it, many companies are struggling to attract and retain a diverse workforce. Becoming a diverse organization is not easy, as it often involves a profound change in corporate culture that is difficult for employees and leadership. The good news is that recent advances in artificial intelligence (AI) and data science promise to help these organizations succeed. Let me explain.
Unconscious bias is the major roadblock to an inclusive business culture
In many organizations, diversity and inclusion remain significant challenges due to unconscious bias. Unconscious biases cause us to have preconceived ideas about what an ideal employee or leader looks like, and our decisions are made accordingly. For example, very often people involved in the hiring process tend to opt for candidates that look and think like them or have a similar background. Unconscious bias impacts key workforce decisions that inform how we lead and manage every member of the workforce, from hiring to promotion and everything in between.
To change these patterns, companies have been investing heavily in programs and training for their employees. However, human habits, especially unconscious ones, are hard to reverse. Most often, the results of these initiatives end up increasing awareness of the biases only temporarily but fail to lock in lasting change.
AI as a change agent for workforce diversity
AI plays a significant role in creating unbiased mechanisms, processes, and tools that influence human decisions. For example, AI-enabled HR systems can be core in helping businesses transform. Human capital management technology enhanced with machine learning can influence key strategy and talent decisions made by HR, executives, line managers, and every member of the workforce. It makes relevant information available at each decision point across a business process, helping the involved parties to rely less on gut feelings and more on job-related data.
For example, machine learning algorithms embedded in tools and applications can help line managers and HR choose interviewer panels that reduce individual bias. Language-intelligent agents can recommend text replacement in job postings to attract a gender-balanced applicant pool. Plus, AI-enabled tools can be used to parse corporate and market data to recommend the right salary range to prevent disparities across employees of different genders or ethnicities. Informed decision making powered by AI removes bias from decisions and supports processes that enable a diverse and inclusive workforce.
A word of caution, however, as proper best practices are required to ensure AI-driven recommendations are free from bias. It is vital that you carefully choose your AI provider and rely on recommendations derived from properly prepared data. Further, you should also ensure that two different teams participate in the creation and validation of machine learning algorithms. This ensures that different mindsets and skills are used to approach a problem, leading to unbiased outcomes. The use of comprehensive and robust data sets in the creation and validation of AI models is also essential as it eliminates risks of making decisions based on biased data.
The ethical implications of AI adoption go far beyond preventing bias. They range from human empowerment to data privacy protection to economics. AI has a tremendous potential to improve lives and transform business outcomes, but it is our responsibility to use it responsibly.
Learn more about Why Artificial Intelligence Will Make Work More Human.