A survey by the Society of Human Resources Management found that 79% of all employers use Artificial Intelligence (AI) and/or automation for recruitment and hiring. The ability of AI to help with targeted searches indicates just one way in which it is also serving a vital role in ensuring that workplaces are more diverse and inclusive. Read on to discover why companies with vision are making AI an integral part of their D&I strategies and policies.

Overcoming Cognitive Biases

Workplaces are riddled with cognitive biases—the irrational “filters” that people use to judge others and make erroneous decisions. Examples of cognitive biases include stereotyping (having over-generalized beliefs about specific groups of people), confirmation bias (interpreting information in a way that confirms our preconceptions), and self-serving bias (blaming external factors when bad things happen and giving oneself credit when good things happen). It is easy to see how biases can translate to poor D&I policies: human beings have biases, and machines don’t.

As such, AI can alert HR and managers to the presence of biases and play two key roles in workplaces: ensuring all qualified candidates have equal access to job opportunities and supporting management in making fair employment decisions.

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For instance, AI can help HR professionals draft inclusive job descriptions, recommend jobseekers for posts they may not have considered, and remove words from CVs that can lead to biased judgments.

Personalized Learning and Training

Much of the workforce’s training takes place online and many professionals are studying to become virtual teachers or tutors in order to form part of the burgeoning gig economy. E-learning is currently worth over $315 billion and it is expected to enjoy a growth rate of 20% between 2022 and 2028.

Studies have shown that the rise of remote work has been a big boon for disabled workers, many of whom would otherwise have difficulties catching transport or otherwise making their way to work. Disabled employees are also benefiting when it comes to e-learning for the same reasons. Where AI comes in is in its ability to personalize learning and training programs to their specific needs.

AI can identify what content, delivery methods, and assessments require adaptation. It can also guide tutors and teachers as to how to make bespoke adaptations so that all employees can make the most of online learning opportunities.

Interpreting Intersectional Data

Intersectionality—the idea that people are often disadvantaged by multiple sources of oppression (including race, glass, and gender)—is an important factor to take into account when creating a D&I policy.

HR departments can use AI technology to dig deep into factors such as education, ethnicity, race, age, and gender—to find existing obstacles to inclusion. These can include candidate pools that are mainly made up of men or people from a certain race.

AI can also help promote inclusive language and communication (providing real-time feedback and flagging inappropriate language), include intersectional identities to improve the accuracy of AI algorithms, and identify specific challenges faced by specific groups in a company.

AI can also be useful in terms of client satisfaction, as it can help companies design products and services that cater to the diverse needs of clients from different intersectional backgrounds.

A word about safety

Even though office-related accidents aren’t as common, they can still occur in spite of our best efforts. In such cases, one of the best approaches is to consult with a workplace injury attorney who will be able to provide suitable assistance and guidance to resolve the aftermath of any type of work-related accident.

AI is an invaluable tool in promoting diversity and inclusion. Three of the many areas it can help in include overcoming biases, personalizing learning, and promoting a deeper understanding of intersectional needs. AI can help from the hiring stage right through to challenges such as retaining staff and preventing them from moving on owing to bias or a lack of equal opportunities.