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Written by Nathan Hewitt

Why Machines make better decisions than humans (oh and why I hate Simon Sinek )

This came up in my feed last week prompting me to share my own 2 cents on why machines are better at hiring decisions than humans.

Did you know that the Wikipedia list of cognitive biases contains 185 entries? This somewhat exhausting article lays out in excruciating detail biases I didn’t know could exist and arrives at the conclusion that they are mostly unalterable and fixed regardless of how much unconscious bias training you attend in your lifetime.

I get asked A LOT about how I can work for a company that sells technology that relies on ‘machines’ to make people decisions.

I will keep it simple … 2 reasons

Because as per above, our biases are so embedded and invisible mostly we just can’t check ourselves in the moment to manage those biases. (I would rather hire women, ideally, mums, who like the same podcast series as me and straight through to offer stage if they like Larry David humour )

And Machines can be ‘trained’ …humans can’t, as easily or efficiently

But the myriad and ever-present news articles about ‘algorithmic bias’ has lumped all machine learning into one massive alphabet soup of ‘don’t trust the machine!

Really? Are we also biased against machines now? I saw Terminator 2 as well and worry about machines taking over the world ….but that’s a massive leap from the practice of bringing data, objective data into the most critical decision you will make as a people leader, who to hire. The divorce rate is for me the proof point that humans suck at making critical people decisions.

I’ve been in the People space for a while. I was lucky enough to work with 2 organisations BCG and the REA Group that value their people above all else. They also value making money and having your engineers and consultants sucked up in recruiting days and campaigns is a massive investment of your scarce and valuable capacity. I have found most companies don’t even know how much it costs to hire one person because no one is tracking the time investment.

We are all time poor and so we often default on hiring based on ‘pedigree’ . Someone has GE on their CV, they must be great as GE only hires great people. That’s a pretty loose /random data point for making a hiring decision

So here is a non data scientist view of why you should trust machine learning to find the right people and when you shouldn’t

First credit to this post which helped me put this into non tech speak .

https://medium.com/mit-media-lab/the-algorithms-arent-biased-we-are-a691f5f6f6f2

Why use Machine Learning at all for decision-making ? Because it underwrites making repeatable, objectively valid (ie data based) decisions at scale.

Value to the organisation:

• Use less resources to hire
• Every applicant gets a fair go at the role
• Every applicant is interviewed
• Hire the person who will succeed vs someone your gut tells you will succeed

How do you ensure there is no or limited bias in the machine learning ?

Take a look at:

– what’s the data being used to build the model
– what are you doing to that data to build the model

If you build models off the profile of your own talent and that talent is homogenous and monochromatic, then so will be the data model and you are back to self reinforcing hiring

If you are using data which looks at age, gender, ethnicity and all those visible markers of bias , then sure enough, you will amplify that bias in your machine learning

Relying on internal performance data to make people decisions, that’s like layering bias upon bias. The same as building a sentencing algorithm with sentencing data from the US court system, which is already biased against black men.

Reality is that machine learning is by its very definition aiming to bias decisions, and removing bias is driven by what bits of training data you use to feed the machine. This means you can make sure the data you train with has no bias.

Machine learning outcomes are testable and corrective measures remain consistent, unlike in humans. The ability to test both training data and outcome data, continuously, allows you to detect and correct the slightest bias if it ever occurs.

Tick to objective data which has no bio data (that means a big NO to CV and social media scraping )

Tick to using multiple machine learning models to continuously triangulate the model vs rely on one version of truth

So instead of lumping all AI and ML into one big bucket of ‘bias’ , look beneath the surface to really understand what’s going into the machine as that’s where amplification risks looms large

Oh and the reason why I hate Simon Sinek …

I don’t actually at all, but if a candidate said that to me in an interview I’d probably hire them for it because I would make some superficial extrapolation about their personality based on it:-

• first it would tell me they watch ted talks and so that eeks of cleverness and learning appetite

• second it would tell me they are confident to be contrarian and that would make me believe that they are better leaders

• third I would infer they are not sucked into the vortex of thinking that culture is the panacea to every people problem.

See how easy it is to make an unbiased hiring decision?

Soon (maybe already) you will be putting yours and your loved ones lives in the hands of algorithms when you ride in that self driven car. Algorithms are extensions to our cognitive ability helping us make better decisions, faster and consistently based on data. Even in hiring.


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Recruitment Platform Sapia shares its ethical framework for AI

Addressing valid concerns in the HR industry about AI, Sapia has released an ethical framework to encourage transparency in the sector

MELBOURNE, Jan 18, 2021 – Sapia (https://sapia.ai/), an Australian technology company that has pioneered transparent AI-assisted hiring solutions, today announced the global release of its Fair Ai for Recruitment (FAIR™) framework to educate HR executives in assessing Ai technology for use in their organisations, as well as act as spark conversations  for Ai developers in the space:  https://sapia.ai/fair-ai-recruitment-framework/

The framework has been released to begin conversations around transparency in HR technology against an explosion of Ai solutions in the sector, with many using algorithms that operate in a ‘black box’. The absence of any form of accreditation of vendors, and the fact that regulation is light years behind tech innovation, has meant a lack of collaboration among vendors to champion Ai ethics in the sector, something Sapia hopes to help change.

The Fair AI for Recruitment (FAIR™) framework :

– Focuses on establishing a data-driven approach to fairness that provides an objective pathway for evaluating, challenging and enhancing fairness considerations.

– Includes a set of measures and guidelines to implement and maintain fairness in AI based candidate selection tools.

-For hiring managers and organisations, it provides an assurance as well as a template to query fairness related metrics of Ai recruitment tools.
-For candidates, FAIR™ ensures that they are using a system built with fairness as a key performance metric.

In launching the framework, Sapia CEO Barb Hyman said: “We have created a framework that we hope can be used as inspiration to ensure that Ai is being used to build inclusive teams – something humans are not capable of doing on their own because we cannot subvert our biases.”

“Our mission is to help HR leaders make bias interruption more than rhetoric, which is why we also published this guide to Making inclusion an HR priority, not a PR one”.

About Sapia

Sapia has become one of the most trusted mobile-first Ai recruitment platforms, used by companies across Australia, India, South Africa, UK and the US, with a candidate every two minutes engaging with their unique Ai chat bot Smart Interviewer.

What makes their approach unique it it’s disruption of three paradigms in recruitment -candidates being ghosted, biased hiring and the false notion that automation diminishes the human experience.

The end result for companies – bias is interrupted at the top of the funnel, your hiring managers make more objective decisions empowered by Smart Interviewer their co-pilot, inclusivity is enhanced, and your hired profile starts to look more like your applicant profile.

Media contacts

Barb Hyman, CEO
barb@sapia.ai

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“Please don’t go” – How to diagnose, cure and prevent Turnover Contagion

“Will the last team member to leave please turn out the lights”

New year, new job.

January is the most popular month for employees to look for new opportunities. But that doesn’t have to mean starting the year with an epidemic of departures.

People leave their jobs for all sorts of reasons.

  • Personal – for instance when a family member needs to relocate.
  • Professional – to get more pay, a promotion, or make a career change.
  • And of course,
  • Organisational – when they are no longer required or suitable for their job.

Any thriving business will want to see a healthy level of turnover in its staff. But what if your people are leaving simply because their colleagues are leaving?

We call this the Turnover Contagion Effect (TCE) and it’s something that every business should care about.

Diagnosing Turnover Contagion

You may have experienced Turnover Contagion yourself. It’s that growing sense that “everyone” in your team is job hunting, and it’s been around for as long as people have worked together.

Your colleagues may not have told you directly that they’re searching. But when there’s a sudden spate of funerals, urgent repair visits or caring for holidaying parents’ goats (all true stories) you may get a sense that something’s up.

Then there are the colleagues who are cagey about letting you see their screens. And of course the ones who quite blatantly tell the rest of the team that it’s only a matter of time before they leave.

However confident and secure you may feel in your role and the organisation, it’s only natural to begin to question your position.

Have your colleagues spotted some major flaw in the business that you’ve overlooked? Do they know something you don’t? Should you put some feelers out there, just in case?

But if you’re observing that disintegrating team from the Human Resources department, you’re probably asking rather different questions.
How did TCE start? Can you stop it spreading further? And how can you prevent it from happening in the first place?

What causes the Turnover Contagion Effect?

Turnover contagion stems from co-workers sharing how they’re feeling and how they’re valued at work. When it’s positive it contributes to more productive working environments and more engaged workers. But when workers are looking around it breeds unrest – it becomes contagious. And once TCE starts it can be hard to stop.

And it seems to be getting worse nowadays, for a variety of reasons;

  • Lower unemployment rates globally make it much easier for your employees to find a new job, and feel more confident in looking for one. There’s also some evidence that the current political climate is discouraging people from looking outside their home countries. So once an employee starts to look, they may find that they are up against far fewer competitors on the shortlist.
  • Social media, and the web in general, have made it amazingly easy to browse for new jobs, even for those who are “not really” looking. LinkedIn is the most obvious place, but there’s a wealth of job sites and careers advice sites that can stir up job dissatisfaction. Social media also spreads the contagion. It’s always been obvious when an unexpectedly large number from one team leave, but now any employee who has reasonable internal connections can spot a trend.
  • Lack of job satisfaction also contributes. Just a few little shared problems in the magic combination that includes pay satisfaction, team relationships and support, communication across, up and down the organisation, the demands of the job, and opportunities for growth and training can add to the spread of TCE.
  • Poor job embeddedness in your company makes things even worse. Studies (1) show that a highly embedded employee is less likely to leave, and very likely to motivate co-workers to stay. A well-embedded employee has many connections within the organisation and the local community, and their job fits with other aspects in their life. The stronger those links, the more committed a worker is to the organisation. Leaving their job would mean sacrificing more than salary. They also risk the loss of friendships, community links and their sense of belonging. So a company where many workers are strongly embedded is less susceptible to TCE. When workers are poorly embedded, far more are ready to leave. They’ll be updating their resumes, watching job postings, applying for new positions, and that inevitably causes an increased individual turnover.

Add these together and you may also experience a fifth factor.

  • Damaged employer reputation. As awareness of increasing staff turnover grows, your reputation as an employer may take a hit. And from there it can become a downward spiral. Your employees notice that more people are on the move. They start to think there’s something wrong with the organisation. They conclude there’s something wrong with anyone who chooses to stay, and they start their own job hunts. The internal damage spreads rapidly over social and traditional media to the local community and across your industry, making it harder to persuade new people to work with you, as well as increasing turnover. It can even start to damage the reputation of the products or services you provide.

Why does Turnover Contagion Effect matter?

When your business starts to suffer from TCE you might think there’s an upside. A long-awaited clear out of rotten wood. A way to make savings on employee costs. A chance for re-organising a dysfunctional department. And yes, all those can be somewhat true.

But whenever you lose a team member there are costs, apart from the obvious ones of losing their production and having to recruit and train a replacement. And these costs far outweigh the benefits.

  1. You lose the training you’ve invested in that person.
  2. You lose their knowledge of your business and all the relationships they’ve built up, internal and external.
  3. You may have to ask other team members to take on their workload while you recruit and then get the new hire up to full productivity – with potential detriment to their normal work.

And as you lose more and more from a team you also risk the engagement and morale of all of their former colleagues. In fact, that’s the greatest risk of the Turnover Contagion Effect – that it spreads further.

As our recent White Paper says (2), “… failing to monitor and moderate turnover can result in leaver behaviour becoming a cultural mainstay of a particular role type, or an accepted norm in the business as a whole.”

Here are 11 Essential Things to Know About Employee Turnover

A Possible Cure for Turnover Contagion Effect

Like most infectious diseases, TCE is easier to prevent than it is to cure. But if you do find that you’re already suffering from TCE, there are a few dos and don’ts.

Don’t

Reduce Social Communication

It’s certainly NOT effective to apply one commentator’s suggestion of trying to “…combat the social environment that stimulates turnover”.

That social side of work may be spreading the contagion, but it’s also the foundation of the strong sense of belonging to a business and a community that encourages people to stay.

Trying to move desks further apart, ban Tweets and Facebook posts or prevent canteen gossip will cause more problems than it solves.

Do

Instead, it may be more productive to consider the root cause of the lack of organisational commitment.

You should be asking:

  • Are supervisors and managers actively supporting the teams experiencing Turnover Contagion?
  • Should you be finding ways to make your business feel a true part of your local community or your industry?
  • Are there working practices and benefits that could be flexed to make workers’ life and work more balanced?
  • Could community engagement or social responsibility programmes help?

… and Probable Prevention for Turnover Contagion Effect

But as mentioned, it’s easier to prevent than cure, so better still is to start at the beginning.

Think about who you hire and how you look after them when they start work.

Are you hiring people who align well with your company culture and values? Are you hiring people with the personality and behavioural traits that make them more likely to stay and perform in your company?

If you’re unsure, that’s where you should start. Try to find out what makes people stay with your organisation. What do your long tenure employees have in common? With your newfound knowledge of your ideal candidate, identify the applicants that fit the bill and prioritise them in your shortlist.

This may sound like a difficult task, but nowadays there are even analytics and technology solutions that can do this for you.

Once you’ve found the right people you still need to look after them and help them commit to your organisation. Introducing each new hire to your company in a motivating induction
process, where they get to know other workers, will give them a strong start.

As they become truly embedded they’re your best hope for preventing future outbreaks of Turnover Contagion.

At Sapia, we help you find your shortlist of candidates who are more likely to stay in your specific business. We combine your data with our workforce and data science to scientifically screen your applicants and predict who is more likely to succeed. And that can also include how well those candidates will fit into your team, your organisation and your community.

References

(1) Felps et al. “TURNOVER CONTAGION: HOW COWORKERS’ JOB EMBEDDEDNESS AND JOB SEARCH BEHAVIORS INFLUENCE QUITTING” © Academy of Management Journal 2009, Vol. 52, No. 3, 545–561

You can try out Sapia’s FirstInterview right now, or leave us your details to book a personalised demo

 

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Scalable career discovery for younger workers

Sapia’s CEO Barb Hyman comments on Australia’s Federal Budget as it relates to the youth.

As Australia rebuilds its economy, investing in the youth is a step in the right direction. However, business and community leaders must guide them towards the right career path, one HR leader said.

“It is comforting and critical that the government has recognised the important need to invest in this younger generation. They are both the worst-affected as a group by COVID in the short term. They are also likely to beat a larger cost of the impact of COVID on the economy and employment opportunities for the next five to 10 years,” said Barbara Hyman, CEO of Sapia.“Despite this, the investment in training only pays off if the individual has a good idea of what jobs they are best suited to. And, we all know, career counselling from school and beyond is pretty much non-existent,” Hyman told HRD.

“The more understanding for the kind of role and environment that brings out the best in an 18- or 25-year-old. The deeper self-awareness they have about their strengths, the more ROI both the government and the individual will get from this massive investment,” she said.

“Scalable career discovery should really be a part of this. R&D backing in this year’s budget should be used. That way, the hundreds of thousands of young people who are making life career choices can do so with confidence. Also, this technology is here now through AI-led personalised scalable career coaching,” Hyman said.

See the full article below.

‘We owe it to the next generation to ensure a strong economy,’ Frydenberg said

The Morrison government is ensuring the next generation won’t be left behind in an economy reeling from the pandemic, Treasurer Frydenberg said.

The Federal Budget 2020 unveiled this week includes incentives to businesses that will hire young Australians, and opens new pathways for upskilling them.

Frydenberg announced a new JobMaker hiring credit, payable for up to 12 months, for companies that will employ workers aged 16 to 35. “It will be paid at the rate of $200 per week for those aged under 30, and $100 per week for those aged between 30 and 35,” he said.

The incentive aims to open 450,000 job vacancies for young workers across Australia. New employees are required to render 20 hours of work per week. Additionally, they must have been receiving support such as JobSeeker, Youth Allowance or Parenting Payment. That is for at least 1 month in 3 months prior to hiring. Read more: JobSeekers are facing rate cuts – and fewer vacancies

Also, the government is also expanding its upskilling programs by allocating $1.2bn to 100,000 new apprentices and trainees. Overall, providing a 50% wage subsidy to businesses that enlist them. Before this, the government had already invested $1bn in creating 340,000 training places for school leavers and jobseekers.

It is also funding the following:

  • 50,000 new higher education short courses in agriculture, health, IT, science and teaching
  • 12,000 new commonwealth-supported places for higher education in 2021
  • 2,000 Indigenous students through the Clontarf Foundation to complete year 12 and pursue further education or find employment

“We owe it to the next generation to ensure a strong economy so their lives are filled with the same opportunities and possibilities we enjoyed,” Frydenberg said.

Read more: JobSeeker plan could cost 145,000 jobs: report

JobMaker credit open to employers hiring younger workers

As Australia rebuilds its economy, investing in the youth is a step in the right direction. However, business and community leaders must guide them towards the right career path, one HR leader said.

Government initiatives for youth!

“It is comforting and critical that the government has recognised the important need to invest in this younger generation. They are both the worst-affected as a group by COVID in the short term. They are also likely to beat a larger cost of the impact of COVID on the economy and employment opportunities for the next 5-10 years” said Barbara Hyman. “Despite this, the investment in training only pays off if the individual has a good idea of what jobs they are best suited to. Furthermore, we all know, career counselling from school and beyond is pretty much non-existent,” Hyman told HRD.

“The more understanding for the kind of role and environment that brings out the best in an 18- or 25-year-old. The deeper self-awareness they have about their strengths, the more ROI both the government and the individual will get from this massive investment,” she said.

“Scalable career discovery should really be a part of this and the R&D backing in this year’s budget should be used. That way, the hundreds of thousands of young people who are making these life career choices can do so with confidence. This technology is here now through AI-led personalised scalable career coaching,” Hyman said.

 

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