LIVE! Candidate Feedback:

I can do much better now Thanks

Yes

Yes it’s very important for further assistance

I was positively surprised by getting this feedback and I find it very helpful In all the ways of use mentioned below ☺️

I did! I found a lot of it very on the mark for me and also some parts way off but that would be somewhat expected. I loved all the bits that make sound great!!! And I can see that the parts that Im not so perfect at could certainly be worked on to be of benefit, so I will look at that aspect, thanks heaps for the analysis I did not expect that! Whats next????

Yes I found this extremely interesting - always love to learn how to be the best version of myself. Always considered myself a team player on a level field full of compassion and empathy for people the environment and animals. Would love to know how my answers resulted in those summaries. Also would be interested if these answers were the cause of me being unsuccessful in moving forward with an opportunity to work for Bunnings. Thank you

Very accurate and true

A great tool to help people realise their strengths and weaknesses and how to improve!

I found the analysis to be interesting and quite revealing. I feel that nearly all of it to be an accurate assessment, but not quite convinced on a couple of points. I'll need to ponder on those points and may come to the same conclusion as your system has determined.

I did find this interesting, and surprisingly accurate.

It's always good to get feedback on applications for employment, and to see if there are areas which could be improved

Very good insight to the O2 world

This was very useful especially the coaching tips, I should listen to the next person before stating my views about something

I found this useful so that the employer has an understanding on who I am before I go in for an interview

I was quite impressed you nearly got it correct keep up the good work

Finding out how and what makes you tick is a positive thing, thank you for that

Hi, thanks for the feedback you shared.

I found this very helpful for interviews and learning more about myself

I enjoy the way Iceland has shown that they are really interested in their employees and who and what their next employees will be like.

I do find this useful. It's always great to get some constructive feedback that I can use to better myself.

It feels like you have observed me for some time because the feedback was very accurate about me. It is very seldom that people understand me like this.

Wow that is a true reflection of who I am.

I found this helpful because, i know what my strengths are and I found it helped me know where I am. I was happy as my confidence shined in the interview. It helped me more be with explaining the situations I’ve been in for examples.

Every word written there should me a highlight of my self and the coach tip was mostly helpful as an eye opener.

Provide information to understand better himself and help to avoid common mistakes

Found it useful as it’s like a mirror I can see my own reflection which I can therefore see areas I could improve.

I found it an quite accurate description of myself. From the insights I have acknowledged the areas in which I could improve

Wow, thank you for my personality insight. I feel you have got to know me , spot on!! Very interesting read and i found your coaching tip extremely valuable . A learning experience i will definitely take on board. Thank you

I appreciate the feed back I am always happy to get a few tips along the way as well as listen to advice I don't generally like to take over in group situations as I am a team player always happy to listen to others and there concerns of new ways of approaching situations

I’ve never heard a summary of myself that way it was really nice

Thanks for the appraisal it pretty well hits the mark on the points raised , and its main point to me is to be more assertive for leadership, I have had management positions with major corporations and it is now a more competitive job market . Thanks for this opportunity Regards Gary

Got to know more about my own strengths and what can be improved.

it helps you find the right job which you

This piece of work was very helpful as it reminds me of more openness and being adaptive to new ideas and changing social, cultural and economic situations. You also hinted on the time and effort when making big decisions which is so interesting. What I would like to express my self on that is that I do take life decisions very seriously and I don't engage into implementation without evaluation of alternatives usually using a decision tree analysis I always try to quantify each and every decision and take into consideration also qualitative information.

It’s always nice to be told that you’re loyal, trustworthy, inventive and even think outside the box. But I feel what is the most important is to be a part of a team, to feel part of a team and to know that team has your back as well.

This was useful to know to give me a insight of how my approach to things comes across

Thankyou for your insight to my personality. Gosh they were pretty much to the letter. I will take the coaching tip on board, reflecting and taking action. Much appreciated

Amazing how answering a few simple questions can give you enough insight to accurately describe me.

I found this very useful as I enjoyed answering questions to the interview and enjoy that I feel like my answers have been really listened to

Hi! Thanks for the process - it was enjoyable and thought provoking. The comment regarding being perhaps perceived as close-minded sometimes is a concern that I will focus on to improve. Likewise the balance between perfection and getting things done more quickly will be something I will keep in mind going forward. Thanks again. Kind regards Graeme

Outlines my qualities and will help in interview process

I found this helpful as some times it's nice for someone to point out good things about someone eles.

I can't believe how accurate it is. I'm very left brained and need to be more creative. Thanks for the tip.

Hiring with AI, fairer, faster and better

Is it time to start trusting the machine?

BY Barbara Hyman

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Machine learning outcomes are testable and corrective measures remain consistent, unlike in humans.

“People are not your most important asset. The right people are.” – Jim Collins, author and lecturer on company sustainability and growth.

“Are the right people in the right roles?” [This is] the single most important factor for leadership success and for organisational success.” – Gail Kelly, former CEO of Westpac

How many research papers do we need to read or edicts from top-class CEOs before we get the message that in every organisation, it all comes down to the people?

Adam Bryant who pens the terrific weekly column, The Corner Office, for the NYT has interviewed a diverse pool of leaders, and a common theme from 99 % of his interviews with CEOs is that success correlates with hiring the best team.

My former boss Tracey Fellows, CEO of the REA Group, was also fond of saying that it is ‘people’ that keeps her up at night more than any other business challenge.

Most hiring in most organisations relies 100 % on people to make those most important decisions. Yet we do so with little objective data. Instead, we have layers upon layers of bias! And to give you an idea of how many there are, here is a whooping full Wikipedia list of cognitive biases for you to check out. This article lays out in great detail a plethora of cloudy, smeary and hazy biases I didn’t know could exist.

It concludes that they are mostly unalterable and fixed, regardless of how much unconscious bias training you attend in your lifetime.


There is no scalable, efficient and reliable way to train us out of our biases. 

Our biases are so embedded and invisible; mostly, we just can’t ‘check ourselves’ at the moment to manage them.


So, how is that diversity hiring program going?

Read: Why a Lack of Diversity is Costing Your Business

In some functions/ departments, your “Hiring for Diversity” may be going very well. However, diversity training and hiring isn’t repeatable, where humans are involved.

And, if humans could be trained out of their biases, we may get more diversity in our new hires. But then, do we know that we are getting the ‘better’ hire from the applicant pool? How CAN you tell if you have no method of reliably testing for what matters for success?

You might say we rely on CVs to give us that ‘insight’ but did you know CVs are usually crafted, designed, worded and reworded to ‘best-light’ the applicant.

Ever appointed an Excel whizz, who on hire doesn’t know a pivot from a concatenate? Or even worse, who cannot apply logic, reasoning and critical thought?

We have all done this – apply crude (biased) filters to screen applications:

  • Blue-chip companies on their CV – tick!
  • Stayed in their role for two years on average – tick!
  • Promoted at least once inside of a (good) organisation – tick!
  • Good school – tick!
  • Impressive referees – tick tick tick!

Because biases appear to be so hardwired and inalterable, it is more straightforward to remove bias from algorithms than from people.

This gives AI the potential to create a future where important insights underpinning decisions such as hiring, are made more fairly.


 

The machine can be trained to help you make repeatable and stable decisions.

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

Algorithmic bias is not the elephant in the room.

Some argue that algorithms themselves have bias. The reality is that machine learning, by its very definition, is aiming to find patterns in large volumes of data, mostly latent, to support decisive actions. Removing bias is driven by what bits of training data you use to feed the machine.

You can ensure there is no (or limited) bias in the machine learning and it is all about two things:

  1. What data is being used to build the model?
  2. What are you doing to that data to build the model?

If you build models from the profile of your 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 is like layering bias-upon-bias. Similar to building a sentencing algorithm with sentencing data from the US court system, which is already biased against black men.

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


To ensure you are using machine learning wisely, only use objective data which has no biodata (that means a big NO to CV and social media scraping).

Test rigorously and adjust to learn continuously. And, be certain to use multiple machine learning models to continuously triangulate the model versus relying on one version of the truth.


Machines are better at learning this stuff.

Unlike trying to solve human bias, machine learning is repeatable, stable, consistent and most importantly, testable. The value to the organisation is of course, immense.

  • Every applicant gets a fair go at the role;
  • Every applicant is assessed;
  • Hire the person who will succeed vs someone your gut tells you will succeed;
  • Use fewer resources to hire;
  • Reduce the cost of hire.

Now that is ticking all the right boxes. It makes the possibility of objective and valid decisions available at scale, a probability.

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.

Soon (maybe already) you will be putting yours, and your loved ones live 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.


To keep up to date on all things “Hiring with Ai” and Machine Learning subscribe to our blog!

You can try out PredictiveHire’s FirstInterview right now – HERE – or leave us your details to get a personalised demo 😀

 

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