HR discussing hiring decision

How that bad hiring decision was made

Have you ever wondered how a bad hiring decision is made? Although we try to hire the most suitable candidate, sometimes bad hiring decisions are made. But this isn’t by coincidence, here are some factors that can influence a hiring decision. 

Was there bias at play? 

Humans unconsciously process 11 million pieces of information per second. In order to manage this mass of data, our brains have had to adapt by creating ‘shortcuts’ to help us make decisions. Without this, we would be paralysed into making no decisions or just random ones. This is cognitive bias.  Here are the 4 reasons why bias could influence a hiring decision.  

  • Too much information – Too many great applicants? Or maybe an applicant’s supporting statement is far too long.  If there is too much information humans are drawn to details that support their existing beliefs. For example, Harvard Business School discovered employers aren’t prejudiced against women because of their gender, but because they have the perception that men perform better in certain tasks.
  • Lack of information – In contrast, when there isn’t enough information our brain fills in the gaps. This includes filling in characteristics of a person or a group from prior history or stereotypes. 
  • The need to act fast – Did the position need to be filled quickly? When we need to make a decision quickly we tend to choose the option that is the least risky to avoid mistakes and preserve our status in a group.   
  • What should we remember? In a world packed with information, our brains need to decide which elements will prove useful in the future. Our minds have created a few methods to enhance storage space, for example, the brain prefers generalisations over specifics because they take up less space.

Learn more about bias here. 

Was the recruiter in a bad mood?

However hard we try to prevent it, our emotions are still a key influence when we make a decision. We know from research, as well as from experience, that it is generally a bad idea to make promises when in a good mood and major decisions when in a bad mood. It is harder to rationalise when we are experiencing negative emotions. The brain is focused on how angry or sad we are instead of the decision at hand.

What time of day was it?

Humans have natural energy highs and lows throughout the day which can impact the decisions they make. This study found that judges would give harsher sentences before their lunch break and were more favourable after, despite the cases being similar. Depending on the time of day a recruiter could make the wrong hiring decision because their energy is low. 

There were too many factors at play 

According to this study, we can only take 7 elements into consideration at once. It might be challenging to make the best decision if there is more than 7 equally qualified candidates for a job, or more than 7 important personal qualities detailed in the personal specification. 

However there is a way to ensure that you make the best decision, regardless of how many factors are at play. A platform like Cognisess Pro is able to consider up to 120 attributes in relation to a candidate’s suitability for a role. This is a lot more information than a human can process. The platform then can present it’s findings in a condensed way to aid HR’s decision making.  

Harness the power of technology

We can’t control the world around us. Sometimes our environment will influence our decisions and other times it could be our unconscious bias, an inherent part of being human. Although we can’t prevent these factors we can ensure they don’t allow you to make a bad hiring decision. Technology is free from human qualities like unconscious bias and energy levels, therefore it can be used as a tool to help us navigate a tricky hiring decision. 

Book a demo with us today if you would like to discuss how Cognisess Pro can help you hire the right person every time. 

Why Amazon’s Ml / AI CV Selection Tool Developed a Bias

Our Chief Scientific Officer, Dr Boris Altemeyer, comments on why Amazon’s AI recruitment tool developed a sexist bias.

It is very interesting to see that a tech giant with, arguably, access to the absolute best talent in this area has admitted defeat. Their AI was simply automating bias, rather than removing it.

Based on our experience, it is not entirely surprising that this occurred. Relying on CV information for job fit is a limited, risky and biased approach. It is affected by factors such as language proficiency, the locus of control (how much you attribute things happening to you as being a result of your own actions), as well as education and social economic status.

Many high profile individuals rely on professional writers to fine-tune or completely ghostwrite their CVs. Therefore using mere a CV as an indicator of potential job performance relies on one – questionable – assumption: what you did in the past and are able to document coherently is indicative of what you are likely to do in a complex and changing environment.

It has been shown in research – meta-studies in particular – that CVs are not a reliable indicator of performance. Therefore, Cognisess starts at the point of which decisions are made: the brain.

The Cognisess Deep Learn framework that underlies many of our features doesn’t take the same approach as an AI CV selection tool. We are interested in learning as much as possible about a person to make a considered decision, whilst assessing their individual potential. However, personal information such as CV data is only a fraction (and actually the least part) that we are interested in.

Objective metrics such as the ability to inhibit automatic responses, paradigm-shifting, or problem solving, are not impacted by your ability to express how good you are at them. Which is why Cognisess use accessible game mechanics to measure them.

Whilst one can argue that there are gender differences between certain aspects of brain preference and function, this is far less of a concern in our complex profilers. If one were to select an employee purely based on one attribute, it wouldn’t paint a full picture of a candidate. However, when we build profilers with up to 140 separate aspects, each of which can have individual weights, target values, and thresholds, these effects arguably become insignificant.

The wealth of data that can be generated on cognition, emotion, behaviour and emotion detection in videos via AI, allows employers to take the crucial step to calibrate what ‘best’ truly looks like. In many cases, the Amazon AI recruiting tool will lead to additional scrutiny on what has caused the bias in workforce diversity including the poorly established or biased KPIs.

Contact us to schedule a demo of Cognisess Pro – the most advanced People Analytics and Assessments Platform in the market today.

Cognisess on digital transformation in the workplace

Zack Weisfeld, MD of the Microsoft Accelerator, is attending the Mobile World Congress this month to join a panel on the topic of “digital transformation in the workplace”. He will be talking about a select number of Microsoft Accelerator start-ups, including Cognisess. Here we share our thoughts on the topic.


–          Are businesses ahead or behind in understanding employee requirements and embracing digital technology?

In our market exploration we’ve found that, in general, businesses are both aware of the new technologies and of the needs of employees. The bottleneck we experience is the gap between knowledge of the needs and issues, and understanding the extent of the impact of the solutions. This makes decision makers hesitant to invest in technology that could be a turning point for a business and make a huge difference to employee satisfaction and wellbeing.

To address this need for knowledge, Cognisess has introduced a Feedback Loop into the Deep Learn™ machine learning platform. This allows continuous tracking of the impact of the recruitment strategy and employee engagement activities delivered through the system. Linking this with 360 Feedback capability, the impact of the technology on the needs of the employees is finally accessible.

 

–          Has the rise of productivity and collaboration tools used by employees over the past few years actually made us more productive?

From what we have seen in terms of technology use in the past few years, the introduction of new services has certainly made a difference to the overall productivity of organisations and people within them. However, the limiting factor here is the initial level of ‘job-fit’ that has been achieved.

A person who would generally be more suited to a different job role, would be much more productive in the role with higher job-fit. Cognisess uses machine learning and advanced job profile matching based on cognitive performance assessments and social cohesion measures to maximise job-fit. This leads to higher performance with higher perceived motivation by the employees, and reduced churn.

 

–          What is the future of assistive technology such as machine learning in the workplace and how will employees embrace the technology?

Assistive technology such as machine learning will change the workplace dramatically in the next few years, and has already begun doing so. Cognisess already uses machine learning to create ‘best-match’ job profilers using millions of data points, including language use and text analysis. This helps athletes enhance their performance by understanding how their brain operates best.

For employees, embracing machine learning provides valuable insights. Having this information available will be a significant improvement to job satisfaction in many areas of work, as guesswork can be taken out of the equation when making decisions. Given the powerful Azure platform and live data feeds to ML, waiting for quarterly reports can be eliminated, as real time data allows for the best decision making background – at any point in time.

 

–          What do you see as the biggest market trends in 2017 and 2018?

According to Bersin, some of the big upcoming market trends include performance management and real-time engagement evaluation. Cognisess has regular feedback built in to the system, alongside online assessments, all accessible by mobile.

There are increasing numbers of tools such as jobs boards, candidate assessments, video interviews and application tracking systems all designed to streamline the process of hiring. And there has also been growth in the area of wellness and fitness monitoring, which Cognisess also includes in its offering.

The field of people analytics has exploded, increasing diversity in the workplace and allowing predictions to be made on which people will perform best in certain roles. In this area, machine learning and automation are the big trends. Cognisess Deep Learn™ machine learning engine enables complex data to be combined and used to predict future success.

 

–          What does the industry need to do better to help companies?

Cognisess offers an all in one solution to significantly reduce the cost and time taken to get recruitment technology into effect within businesses.

In a recent article from ERE Media, Unilever described their use of a multi-platform process. The first step is an application and LinkedIn sync, the second a Pymetrics assessment, the third a HireVue video interview, before a full day even at Unilever. This all makes up a two-week process.

In contrast, Cognisess provides the ability to complete an application that includes comprehensive assessments, written information and a video interview all in one, reducing time and cost.

 

–          How do you see the employee experience evolving and what technologies will they be drawn to in the future?

Cognisess’ all in one approach not only benefits employers, but candidates too. Accessing one simple and intuitive platform where they can follow through clear steps to fill in their details, complete assessments, and record video interview responses.

And once employed, these individuals can go on to receive 360 feedback from their colleagues, monitor their own health and wellbeing, and continually monitor their skills and improve their self awareness and personal development.

 

For more information on the Cognisess platform and the Cognisess Deep Learn™ machine learning engine, contact us at support@cognisess.com.