We know that unconscious bias occurs when we make quick judgements of people and situations without realising our preconceived ideas. These biases can be influenced by our background, gender, cultural environment and past experiences and whilst we might not be aware of these views, their impact can still be considerable.
Recent research from Deloitte found that teams that are both cognitively and demographically diverse perform better and are more profitable. Diversity of thinking is better for creativity, innovation is enhanced by about 20 percent and decisions are easier to implement achieving buy-in and trust.
Technology of course can help startups overcome unconscious bias to a degree, but as Amazon discovered, its AI recruiting tool was perpetuating the gender gap in the tech sector, not bridging it. Given only 13.5 percent of people currently working in machine learning globally are women, it’s hardly surprising AI technologies have gender and other biases built in. Despite unconscious bias being inevitable, here are five ways startups can ensure it doesn’t adversely affect your recruitment:
1. Hold a discovery workshop
Before you embark on the recruitment process, facilitate a discovery workshop to identify what skill gaps currently exist in your startup. Ask yourself and your team what culture you want to continue fostering and how new hires fit into your growth plans. Examine the desired behaviours new hires will need to succeed and make sure you’re not inadvertently disadvantaging specific individuals or demographics.
2. Write inclusive job advertisements
Open and conversational advertising rather than punchy adverts asking for ‘ninjas’ or ‘unicorns’ is important. Men will apply for a job when they meet 60 percent of the qualifications, whereas women will apply only if they meet 100 percent of the qualifications. To attract more women into STEM roles and from ethnically diverse backgrounds, you need to write advertisements that demonstrate the organisation values inclusion and is proactive in trying to address workplace imbalances. There are tools such as Gender Decoder or Textio that can check the wording in your job descriptions for gender-biased language.
3. Explore new places
When it comes to looking for potential hires, widen your search and consider targeting people who might be working in other sectors. Also consider the possibility of hosting an event for people to come and learn more about your startup, but make sure you host the event at a time that doesn’t exclude people, for example breakfast events are tough to attend for working parents who have to do the school run.
4. Make sure a female candidate is on every interview shortlist
We know that the tech industry is male dominated, and we recommend that startups adopt a policy of having a female candidate included in every interview shortlist. We’ve had good success with this approach, because when you get to the interview stage, attitude and cultural fit is more apparent. It’s also important to use a structured interview process, with behavioural interviewing questions, to ensure that each candidate is given a similar experience and evaluated against the same criteria. When determining whether the candidate fits those criteria, use specific examples from the interview to back them up.
Whilst technology can help startups overcome unconscious bias, don’t rely on it. Nothing replaces meeting people face to face and working with hiring experts who know their respective industry sectors. Be prepared to look in new places for potential team members and consider people from a wide variety of backgrounds who might not have the ‘exact’ experience you’re looking for, to ensure greater diversity and representation.
You can read more about gender bias and hiring here.
Sonia is the Head of Talent Advocacy at affix. Her role is to lead the team in its endeavour to deliver the best candidate experience as they enter the crazy world finding their happy (work) place. With over 16 years of experience, her focus is to provide continuous improvement to the entire recruitment process, to ensure greater efficiencies, improved customer experience and better career outcomes. Sonia also manages assignments in data science, product, marketing and sales.