Arsham Ghahramani, PhD, Co-founder and CEO of Ribbon – Interview Series

Arsham GHHHRAMANI, PhD, is the co -founder and CEO of Ribbon. Its headquarters in Toronto and UK origin, ghahramani is a background in both artificial intelligence and biology. His professional experience extends to a range of areas, including high frequency trading, employment and biomedical research.

GHHAHRAMANI began to work in the field of artificial intelligence around 2014. He completed a doctorate at the Francis Institute of Crick, as the early forms of artificial intelligence applied to study the regulation of cancerous genes – before the term “AI Tawnidi” entered the prevailing use.

It is currently a pioneer, a technical company that focuses on speeding up the recruitment process. Ribbon raised more than $ 8 million of financing, supported more than 200,000 job seekers, and continued to develop its team. The statute aims to make employment 100x faster by combining artificial intelligence and automation to simplify employment tasks.

Let’s start at the beginning – what inspired you to find the tape, and what is the moment “AHA” that made you realize that the employment has been broken?

I met the founders of the participant Dave Fu while we were in Ezra-he was the head of people and talents, and I was head of machine learning. Since we quickly expanded my team, we felt constantly pressing up quickly, however we lacked the right tools to simplify the process. I was early in artificial intelligence (I completed the doctorate in 2014, a long time before becoming prevailing artificial intelligence), and I had an early understanding of the effects of artificial intelligence on employment. I have seen close shortcomings and challenges in traditional employment, and I knew that there should be a better way. This awareness prompted us to create a tape.

I have worked on Amazon’s automatic learning roles, Ezra, and even in the trading of algorithm. How did this background formed the way you dealt with the construction of the tape?

In Ezra, Amnesty International has worked on health technology, where the risks could not be higher – if the artificial intelligence system is biased, this may be a matter of life and death. We spent a lot of time and energy while making sure that our artificial intelligence was not biased, as well as developing ways to detect and alleviate bias. These technologies brought to the tape, where we use these technologies to monitor and reduce the bias in the interview, which ultimately created a more fair recruitment process.

How did your experience as a candidate and director of employment affected the product decisions you made early?

Finding a job is a stressful process for young candidates. I remember, not long ago, being a beginner candidate applying for many jobs. It has become more difficult since then. In the tape, we have deep sympathy for job seekers. The sound of artificial intelligence is often the first communication point between the company and the candidate, so we work hard to make this experience positive and rewarding. One of the ways we do is to ensure chat with candidates with the same artificial intelligence throughout the entire recruitment process. This consistency helps build confidence and comfort – contrary to the traditional processes in which candidates are passed between many people, our artificial intelligence provides a fixed and familiar presence that helps candidates to feel more comfortable while moving through interviews and assessments.

Ribbon’s Ai performs interviews that feel more law than text robots. Tell us more about Ribbon’s adaptive interview flow. What kind of understanding in the actual time happens behind the scenes?

We have built five automated learning models at home and integrate them with four models available for the public to create a tape interview experience. Behind the scenes, we constantly evaluate the conversation and collect this with the context of the company, professions pages, public features, CVs, and more. All this information comes together to create a smooth interview experience. The reason is that we combine a lot of information is that we want to give the candidate the experience of the closest to a human recruiter as possible.

You can highlight that five minutes of sound can match an hour of written inputs. What kind of signals do you pick up in these sound data, and how is they analyzed?

People generally speak very quickly! Most of the functional requests are very boring, making you fill in many different models and multi -options questions. We have found that 5 minutes of natural conversation equivalent to about 25 multi -options questions. It is difficult to overcome the intensity of information in the voice conversation. Moreover, we collect other factors, such as language mastery and communication skills.

Ribbon also works as an artificial intelligence writer with automatic tools and registration. What role does the ability to explain in making these data useful – and fair – for employees?

The interpretation is at the heart of the ribbon approach. All the result and the analyzes that we constitute always are related to its source, making artificial intelligence very transparent.

For example, when we register a candidate about their skills, we refer to two things:

1. The original job requirements and
2. The exact moment in the interview mentioned by the candidate is a skill.

We believe that the interpretation of artificial intelligence systems is very important because at the end of the day, we help companies make decisions, and companies that want to make decisions based on tangible data. Something we believe is it is extremely important to both fairness and confidence in the employment that is moved by artificial intelligence.

Bias in artificial intelligence employment systems is a great concern. How is the tape designed to reduce or reduce bias with the appearance of senior candidates?

The bias is a critical issue in employing artificial intelligence, and we take it seriously in the tape. We have built an interview with artificial intelligence to evaluate candidates based on measurable skills and competencies, which reduces the subjectivity that often provides bias. We regularly review our artificial intelligence systems for fairness, use various and balanced data groups, and integrate human control to capture and correct potential biases. Our commitment is to distribute the best candidates fairly, ensuring fair recruitment decisions.

Candidates can meet at any time, even at 2 am. How important is flexibility in adding a democratic character to access jobs, especially for disadvantaged societies?

Flexibility is the key to the democratic character to reach jobs. It allows interviews with Ribbon always for candidates to participate at any suitable time for them, which spoils traditional barriers such as conflicting timetables or limited availability, which is especially useful for working parents and those who suffer from unconventional hours. In fact, 25 % of the tape interviews occur between 11 pm and 2 am local time.

This is especially important for disadvantaged societies, as job seekers face additional restrictions. By enabling access to the clock, Ribbon helps ensure that everyone has a fair opportunity to display their skills and secure job opportunities.

The tape is not only related to employment – it is about reducing friction between people and opportunities. How does this future look like?

In the tape, our vision extends beyond effective employment; We want to remove friction between the individuals and the opportunities that suit them. We expect a future as technology links the smoothness of talents with roles that are completely in line with their capabilities and aspirations, regardless of its background or network. By reducing friction in job mobility, we enable employees to grow, develop and find satisfactory opportunities without unnecessary barriers. The fastest internal mobility, low rotation, and ultimately better results for both individuals and companies.

How do you see artificial intelligence transform the process of employment and the broader job market during the next five years?

Artificial intelligence will reshape employment and the broader labor market in the next five years. We expect the automation that artificial intelligence drives will simplify the frequent tasks, which frees the employees of employees to focus on deeper candidates’ interactions and strategic employment decisions. Artificial intelligence will also enhance the accuracy of the candidates matching the roles, accelerate employment schedules and improve the experiences of candidates. However, to achieve these benefits completely, the industry must give priority to transparency, fairness and moral considerations, ensuring artificial intelligence becomes a reliable tool that creates a more fair work scene.

Thank you for the wonderful interview, the readers who want to know more should visit the tape.