Building a GPS for Human Skills
An Interview with Kian Katanforoosh, CEO & Founder at Workera
The biggest constraint on performance is talent, not financial resources. Financial resources help you pay for the right people but only if you can first find them. Second, you must know how to help them put their best foot forward, and finally you have to then nurture & support them effectively.
Examples of this phenomenon abound from elite sports to the world of business. You simply cannot pay your way out to exellence in the talent market. Just ask Chelsea football club.
Kian Katanforoosh and his team at Workera are attempting to tackle the crux of this problem by building a GPS for human skills. Their technology allows them to measure 10,000 skills across 60 domains. They provide their partners both with the ability to assess talent and the learning pathways required to upskill that talent in line with the company’s strategy.
Kian himself is an Iranian-French founder, who moved to the US to do his graduate work in Computer Science at Stanford before working with Andrew Ng to launch DeepLearning.AI where they taught millions of people critical AI skills. As an immigrant founder, he knows a thing or two about the need to find and harness talent.
I recently sat down with Kian to talk about assessments and the future of learning considering recent developments. The interview has been condensed for brevity.
1. What motivated you to start Workera?
I’ve always been interested in unlocking human potential.
Education is a powerful key in that regard. It can help people change their lives. It is a foundational solution to a lot of problems upstream. If Workera can help people fulfil their potential, then we can improve the quality of their lives across the board.
I believe that the real gap in achieving this is not around content creation anymore - the cost to create and distribute content is going to zero - but about pinpointing where learners are in their upskilling journey.
With that belief, we paired psychometrics with AI to unleash the power of assessments. Assessments have historically been used for summative purposes, but we focus on deploying formative assessments to accelerate people’s ability to identify key gaps in their understanding and the best paths towards remedying these gaps.
2. What is Worker’s vision for the future of learning and how do you think about assessment?
The grand vision is to help humanity achieve its fullest potential.
Imagine we had a validated system that allowed everybody to always at any point time know where they stand and how they compared to their peers.
Furthermore, at a macro level, imagine employers and policymakers could also see where people of a certain skill are located. All relevant parties would be able to understand the supply and demand of key skills.
Football is a great analogy for our vision.
Professional football clubs measure everything about their talent at a very granular level and are able to benchmark that against the wider context of the leagues they play in. They know the speed of every player, the likelihood of injuries, player precision with each foot etc. All that data is already in sports, but it's not yet in the wider talent market. It will come to enterprise over the next 10 to 20 years.
Once that happens, enterprises will realize precise skills measurement that can allow them to hire the best workforce and manage it effectively.
I think it's just a matter of time before we get there, and we want to be one of the leading companies that push towards this vision.
3. What do you think is the future of assessment?
Assessment requires two different technologies - delineating a skills ontology and evaluation of the identified skills and subskills.
The holy grail would be to measure people in situ. You want to observe them in work-like environments working on projects. We are not there yet, but that is the future we want to build towards.
What is possible today is to take a project and convert it to its granular component skills that we are capable of measuring. You then proceed to measure people on the ontology not the overall project.
4. How do you think about or measure the transfer of skills to real world contexts?
Measuring and demonstrating transfer is incredibly difficult. Most if not all enterprises don’t do this well and end up having to rely on a lot of proxies – which for our clients ends up being Workera itself.
To validate our measurements, we use expert senior interviewers to assess candidates in blind experiments. We assess the individual and rank them on our criteria, and then compare our results with the expert interviewer.
It will take a couple of years to get this perfectly, but I believe we are on the right path.
5. You recently raised a series B amidst all the excitement about how AI will change learning. Where do you see the impact of AI on assessment & Workera?
Most importantly, AI will exponentially improve how we learn and what skills we can measure - and by extension predict.
We’re essentially building a graph of skills that anyone could benefit from. Language models, when paired with our own data and expertise, improves our ability to predict skills. We can do this by better understanding the intrinsic relationships between skills development and learning processes. I think this will have the biggest impact on personalized tutoring and mentoring.
Second, there will also be productivity boosts across different jobs. For example, we’ve seen that using Co-Pilot - boosts developer productivity by 30 - 40% in various software and data tasks. This boost in productivity will in turn change what skills we need as employers and as a society.
I hope that you enjoyed this interview with Kian - any and all thoughts are welcome. You can find me on Twitter.
Finally, welcome to all the new subscribers that have joined since the last issue. Please do reach out if you have any thoughts or comments and don’t forget to share with your friends.
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