How to use human-machine partnerships to build stronger startup teams

The first few hires are vital for startups. You need to find people who are not only talented and reliable, but will help you build the right culture as your business grows.

There’s a lot of pressure on startup founders to get recruitment right – but that’s easier said than done. You might be recruiting for the first time and having to learn about the hiring process as you go, or a solo founder relying exclusively on your own judgment. 

It’s a minefield, and one of the biggest challenges that founders face. Yet with human-machine partnerships, it could soon be a problem of the past. 

Human-machine partnerships sound complex, but the idea is very simple – rather than using either humans or technology to complete tasks, the two can collaborate to create better results than either could do alone. For example, Microsoft’s use of AI in recruiting focuses on reducing administrative tasks, speeding up the screening process, and minimizing biases. By automating routine tasks like scheduling interviews and answering candidate queries via chatbots, recruiters can focus more on strategic aspects of hiring. AI-driven tools also help in pre-screening candidates, especially for roles with straightforward requirements, thus reducing the time to fill positions (Korn Ferry | Organizational Consulting) (RecruitingDaily).

Emerging technologies are already transforming workplaces, whether it’s using inteligência artificial to be more efficient or multi-cloud to improve flexibility. These new technologies will also be used to help businesses find, assess and hire talent more effectively – here’s how.

Reducing bias in human decision-making

Even with the best intentions, cognitive bias will almost always creep into hiring decisions. There are lots of benefits to being able to rely on intuition and make quick decisions in other areas of your life, but this behavior is detrimental when you’re recruiting.

Whether it’s reading applications or conducting interviews, our perceptions can be influenced by a huge number of biases, including:

• Confirmation bias: Focusing on and seeking out information that supports your initial beliefs about a candidate
• Halo effect bias: Allowing one positive aspect of a candidate to overshadow their other attributes (e.g. hiring them because they worked at a company you admire, not because they’re the best person for the role)
• Affinity or similarity bias: Gravitating towards people who share similar backgrounds, interests or characteristics as you

These biases all create stumbling blocks when building effective startup teams. Diversity breeds innovation, and overlooking great candidates will put you at a disadvantage when it comes to staying competitive.

Human-machine partnerships can minimize this bias and create a more successful hiring system. AI can be used to screen and shortlist the most qualified candidates, bypassing characteristics like age, gender and class which typically lead to bias. Then, you can conduct an in-person interview to assess more ‘human’ skills like active listening and empathy.

Many businesses are already using technology like AI in recruitment, but it will become even more common in the future. Up to 67% of business leaders expect to use new technologies to create equal opportunities in recruitment by removing human bias from decision-making. 

Building up a richer picture of candidates

In addition to reducing bias, new technology will also help founders to build up a much richer picture of applicants than what’s on their résumé. 

Algorithms can be used to assess someone’s hobbies, interests and experiences and draw conclusions based on how similar candidates have performed at other businesses. For example, a specific interest could indicate higher levels of intellectual curiosity or stronger leadership potential.

This will provide insight into who would be most likely to perform best in the role, but also help you to identify hidden strengths in candidates. 

Many great candidates struggle to express themselves in written applications or don’t realize they possess certain skills. New technologies bring these abilities to light, allowing you to broaden your talent pipeline, connect with people from a wider range of backgrounds and build a more inclusive, powerful team.

Optimizing your team for the future

Human-machine collaboration can also help you predict and plan your hiring needs in advance. Rather than having to scramble and hire for key roles last minute, you can start building your network and connecting with potential candidates much earlier.

With new technology, startups can conduct the same in-depth market analysis that larger companies often benefit from. This will transform how you hire and train employees, and shape the rewards you provide to retain them for the long term. 

This includes:

• Identifying skills gaps in your current team. Technology will be able to analyze performance, skills and project outcomes to spot skills gaps and suggest training opportunities.

• Predicting trends and future skills needs. By looking at wider industry trends and activity, technology can provide insight into the types of jobs that will be most in-demand in two to five years’ time. This advanced visibility will allow you to upskill your team or plan for future hires.

• Finding adjacent skill sets. If you’re struggling to recruit for a specific role, AI can find candidates (or even current employees) with adjacent skills which could be transferable with some extra training.
• Highlighting at-risk employees. Technology can track the value of certain skills in the market to help you understand which employees might be targeted by other companies and hired elsewhere. As a result, you can be proactive about offering pay rises or other incentives to retain your best talent.