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Click the candidates to see their CVs

Rejected Candidates

Respond to Email

Re: Candidate complaint

From: software-engineer@bestfit.com

Subject: Hiring Algorithm

You asked us how we can hire faster. So we built a hiring algorithm using machine learning. Basically, we will teach a computer to hire like you, but way faster!

First, the algorithm will read through past applicants' CVs and whether they were hired or not. It will then learn what makes a candidate good or bad by copying your hiring decision process!

It's impossible for the program to know good or bad candidates without human input - we first need to give it a lot of data to learn from.

I need your help: can you send me the CVs of all applicants you've evaluated so far? Click on the file named "cv_all.zip" on your desktop

Thanks! Machine learning algorithms get more accurate with more data, so here's what we'll do: use big tech companies' data. They have huge applicant records, so we can merge our CVs with theirs and train our model! Choose a company you think hires smart people.

Thats it! We can now train the algorithm with a lot of past data and put it to use!

Great, let's train it!

From: software-engineer@bestfit.com

Subject: Hiring Algorithm Ready!

Our algorithm has been trained. Your job is automated now, so enjoy the ride!

Great.

From: software-engineer@bestfit.com

Subject: Hiring Algorithm

We're trying to figure out what's wrong with the algorithm.

Let's break down its decisions by orange and blue?

Here they are; what do you think?

Lets find out how! Do you remember how we first trained the algorithm?

Look at our data from manual hiring:

We should have also checked the quality of the big company dataset you sent me! How am I supposed to understand hiring decisions? I'm a software engineer!

We should've worked together more and been more careful...

Taking A Step Back

As a recruiter, which of these attributes did you value the most?

This is a simplified simulation, but we hope it got you thinking. Now imagine how difficult it is to choose for a real-life recruiter!

When there are many unknowns, people tend to rely on their gut feelings, which is just an expression of their biases and preconceptions.

You might not be consciously discriminative, but in the early days of your company you received more highly qualified orange applicants. The unknowns and the biased environment can make well-intentioned decisions biased. This is what the industry needs to realize.

Training the Biased Algorithm

When the engineering team contacted you, they asked you for your decisions, in cv_all.zip , because a machine learning (ML) algorithm requires human input.

That means if you had biases, the software would replicate them! But what if you were as objective as you could be?

Your data alone wasn't enough to build a ML algorithm, because machine learning works only on large amounts of data. That's why the software engineer asked you to choose a larger dataset. The problem is, all datasets are built by humans who tend to be biased.

In this case, it largely consisted of applicants from Orange Valley, where more people were historically allowed to work in tech.

Behind the Difficulties

Can we disregard race or gender?

There are no buttons on ML algorithms and the input data is often difficult to debias. While applicants don't put race or gender explicitly on their CVs, they are often manifested through the colleges, communities, and organizations certain demographics are usually a part of.

When a program learns from years of data, we need to question the data it is learning from. Just because a decision is presented as 'automated' doesn't mean it is right or objective.

Your startup Bestfit might've failed today, but there's no reason our societies should! Head to our website to learn more. We hope it'll make you discuss and ask questions.

Hey there this is some text

Dismiss

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Click the candidates to see their CVs Respond to Email Re: Candidate complaint From: software-engineer@bestfit.com Subject: Hiring Algorithm You asked us how we can hire faster. So we built a hiring algorithm using machine learning. Basically, we will teach a computer to hire like you, but way faster!

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Australian Framework for Generative AI in Schools

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CSER STEM Professional Learning | University of Adelaide

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The Supporting Artificial Intelligence in Schools Initiative is an Australian Government Department of Education program aimed at engaging students and supporting teacher professional development in this critical area.

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It’s been over 12 months since the first blog post about the AI Assessment Scale, and a lot has changed, both with the technology and with our understandings of how it impacts assessments in …

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Finding the best educational AI tools is essential for effective teaching, learning, research, and career development. Discover top-rated tools and resources to enhance educational experiences and foster academic growth.

Scroll to the right
for more categories ->

Libby talks to your leads, qualifies them, and gets them booked on your calendar.

Coinfeeds helps users stay on top of the latest crypto news and coin-specific updates.

Architect Render is a cutting-edge web app that uses Artificial Intelligence to generate 3D renderings of architectural and interior design projects in seconds.

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A ranked list of the best AI-powered Education tools. Browse a variety of AI education software. Transform the learning process for students and educators.

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How AI Could Save (Not Destroy) Education | Sal Khan | TED

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Skip to main content

These modules were developed in collaboration with Microsoft.

As generative AI (GenAI) becomes an increasingly important tool in education, it is important for teachers to develop an understanding of its capabilities and limitations. These two modules equip teachers with the knowledge and skills to use GenAI effectively in the classroom, enabling them to enhance their own digital literacy and help build digital literacy skills in their students when using GenAI tools such as Copilot. By building teacher readiness and providing practical strategies, this course supports educators in preparing students for appropriate use of AI in learning and everyday life.

Each self-paced module is expected to take around 60-90 minutes, is free and requires no log-in.

A certificate is available for download on completion of the module.

AI readiness: Preparing teachers for safe and effective use of GenAI

The module aims to increase teacher readiness when using generative AI (GenAI). It builds teachers' own digital literacy around GenAI and equips them to develop their students' digital literacy capabilities.
Who is this for:
Australian F-12 teachers interested in learning about and exploring the use of generative AI for streamlining admin tasks and personalising learning, safely and responsibly.

Aligned to: Australian Professional Standards for Teachers

Developed in collaboration with Microsoft.
Start module

AI implementation: Strategies for guiding students in safe and effective use of GenAI

Building on the foundations laid in the AI Readiness module (designed for teachers), the second module flips the focus - teachers now guide their students through similar activities, adapted for the classroom. With teacher understanding already in place, the emphasis is now on practical, age-appropriate classroom implementation.
Who is this for:
Australian teachers with students aged 13+ who want to integrate generative AI tools into their classrooms safely and responsibly.

Aligned to: Australian Professional Standards for Teachers

Developed in collaboration with Microsoft.

Coming Soon

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Gen AI readiness and implementation modules

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These modules were developed in collaboration with Microsoft and help teachers to develop an understanding of generative AI (GenAI) and its capabilities and limitations.

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This AI framework was developed alongside Chris Cormack, Kai Tahu, Kāti Māmoe, who guided us step by step to support schools in integrating artificial intelligence into teaching and learning.

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How schools can use AI to improve student attendance

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AI could help support attendance strategies with data analysis and more for schools looking to improve student engagement.

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What generative AI is

'Generative artificial intelligence' is a term that covers a range of tools that have been trained using huge sets of data to create new content. It is also called 'AI' and 'GenAI'.

Artificial intelligence has been around for a while, powering technology like predictive text. It is quickly becoming more widely available to more people, in free-to-use and paid tools and services.

Resources

These resources from trusted sources can help you learn more about generative AI.
Introduction to artificial intelligence - Tāhūrangi He Kōrero Whakataki ki te Atamai Rorohiko - Tāhurangi Exploring Generative AI in a NZ classroom - Netsafe
What to think about when using AI tools

Check the output

AI can create content that seems plausible but contains nonsensical or incorrect detail. Whenever you use AI, make sure that you are reviewing and checking the outputs.
An introduction to the role of Artificial Intelligence in classrooms and schools - The Education Hub
Don't use personal data

Most free AI tools use the prompts you put in to continue to train the model - what you put in. The AI uses to improve its output. Don't use personal data when you use AI tools, as what you put in may be reused.

New Zealand's Office of the Privacy Commissioner has released expectations for people and organisations using generative AI. Principals and teachers should keep these guidelines in mind.
Generative artificial intelligence - Office of the Privacy Commissioner
Cultural bias

AI models are trained on huge amounts of data from different countries and cultures. This means most AI models are built on dominant cultures and languages. The tools may not accurately reflect indigenous knowledge. From a New Zealand context, they are likely to be weak on Mātauranga and Te Reo Māori, as well as Pacifica languages and Polynesian cultures.

Read terms and conditions

Carefully read the terms and conditions of use. Many AI models will reuse your prompts and the data you provide it to continue to learn and train. Make sure you do not enter copyright, confidential, personal, or sensitive information into these models.

Talk about it and make a policy

Discuss with your staff how you can use AI at your school and what rules and guidance you need to put in place for different contexts.

Teachers using AI

AI in education should improve teaching and learning, supporting knowledgeable and skilled teachers.

Human teachers must:

remain central in students' education

take responsibility for students' learning.

Reviewing work with AI tools

Teachers and the school are responsible to make final decisions on learners' work. Teachers should avoid using AI tools to mark work. AI systems have not seen enough work by young people in the context of New Zealand's national curriculum to have a good understanding of what is expected and may be unfair or discriminatory.

Students using AI

GenAI gives us opportunities to enhance teaching and learning, but when it comes to assessment, its use needs to be restricted to ensure a student's work is their own.

NZQA has guidance on AI and when its use is acceptable in assessment.
Guidance on the acceptable use of Artificial Intelligence - New Zealand Qualifications Authority
Age restrictions on use of AI

As with any digital tool, teachers and students must abide by the terms and conditions of the tools they're using.

Several AI tools have age restrictions on their use. For example, to use ChatGPT you must be at least 13 years old, and if you are under 18 you must have your parent or legal guardian's permission.

The terms of use for ChatGPT and any services using it are clear: you must not send it any personal information of anyone under the age of 13.

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Guidance and resources for education professionals on the use of artificial intelligence in schools.

# data[].attributes.attachment_link.readable_text
What generative AI is

'Generative artificial intelligence' is a term that covers a range of tools that have been trained using huge sets of data to create new content. It is also called 'AI' and 'GenAI'.

Artificial intelligence has been around for a while, powering technology like predictive text. It is quickly becoming more widely available to more people, in free-to-use and paid tools and services.

Resources

These resources from trusted sources can help you learn more about generative AI.
Introduction to artificial intelligence - Tāhūrangi He Kōrero Whakataki ki te Atamai Rorohiko - Tāhurangi Exploring Generative AI in a NZ classroom - Netsafe
What to think about when using AI tools

Check the output

AI can create content that seems plausible but contains nonsensical or incorrect detail. Whenever you use AI, make sure that you are reviewing and checking the outputs.
An introduction to the role of Artificial Intelligence in classrooms and schools - The Education Hub
Don't use personal data

Most free AI tools use the prompts you put in to continue to train the model - what you put in. The AI uses to improve its output. Don't use personal data when you use AI tools, as what you put in may be reused.

New Zealand's Office of the Privacy Commissioner has released expectations for people and organisations using generative AI. Principals and teachers should keep these guidelines in mind.
Generative artificial intelligence - Office of the Privacy Commissioner
Cultural bias

AI models are trained on huge amounts of data from different countries and cultures. This means most AI models are built on dominant cultures and languages. The tools may not accurately reflect indigenous knowledge. From a New Zealand context, they are likely to be weak on Mātauranga and Te Reo Māori, as well as Pacifica languages and Polynesian cultures.

Read terms and conditions

Carefully read the terms and conditions of use. Many AI models will reuse your prompts and the data you provide it to continue to learn and train. Make sure you do not enter copyright, confidential, personal, or sensitive information into these models.

Talk about it and make a policy

Discuss with your staff how you can use AI at your school and what rules and guidance you need to put in place for different contexts.

Teachers using AI

AI in education should improve teaching and learning, supporting knowledgeable and skilled teachers.

Human teachers must:

remain central in students' education

take responsibility for students' learning.

Reviewing work with AI tools

Teachers and the school are responsible to make final decisions on learners' work. Teachers should avoid using AI tools to mark work. AI systems have not seen enough work by young people in the context of New Zealand's national curriculum to have a good understanding of what is expected and may be unfair or discriminatory.

Students using AI

GenAI gives us opportunities to enhance teaching and learning, but when it comes to assessment, its use needs to be restricted to ensure a student's work is their own.

NZQA has guidance on AI and when its use is acceptable in assessment.
Guidance on the acceptable use of Artificial Intelligence - New Zealand Qualifications Authority
Age restrictions on use of AI

As with any digital tool, teachers and students must abide by the terms and conditions of the tools they're using.

Several AI tools have age restrictions on their use. For example, to use ChatGPT you must be at least 13 years old, and if you are under 18 you must have your parent or legal guardian's permission.

The terms of use for ChatGPT and any services using it are clear: you must not send it any personal information of anyone under the age of 13.

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Guidance and resources for education professionals on the use of artificial intelligence in schools.

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AI Use for Orewa College Students Version 2

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AI Use for Orewa College Students Version 2