Predictions Series 2022: Women Leaders in AI Would Rise through the Ranks
The discussions around the role of women leaders in AI have always piqued the interest of the technology industry. With growing interest in coding for women, companies have become more sensitive in how they embrace inclusivity to close gender gaps in technology leadership roles, especially in AI and machine learning domains. Organizations hire women leaders in AI to bring a balance to overall business outcomes, encouraging young women professionals to take up more coding jobs in an industry that suffers heavily due to a severe lack of skilled workforce and leaders. Today’s predictions series chat features one of the top women leaders in AI who has been encouraging young female professionals to take up challenging AI projects and showcase new-gen career pathways. We have Leah Forkosh Kolben, the co-founder & CTO at cnvrg.io.
We spoke to Leah about fascinating developments in the field of AI, machine learning and data science, and the future of embedded AI in business intelligence tools. Here’s what Leah answered.
Hi Leah. Welcome to AiThority.com’s Predictions Series. You are among the top women leaders in AI space. Could you tell us about your fascinating journey in AI and data science?
Leah Forkosh Kolben: I had developed my passion for technology at a very young age. By High School, I had already completed a BSc in Mathematics and Physics, and continued along this path in the Israel Defense Force (IDF) Intelligence unit, as an electrical engineer.
Following my 3-year service as an engineer, I advanced my learning, earning a BSc in Computer Science at the Hebrew University of Jerusalem while simultaneously working as a software team leader at WatchDox, which was later acquired by Blackberry. In my most recent position, before founding cnvrg.io, I lead the startup, Appoint, as CTO – and then followed my career consulting enterprises on AI and Machine Learning.
That’s an inspiring journey. Which area of science are you most excited about in the AI and Machine Learning space?
Leah: MLops and Automation.
I think, in 2022, MLOps will introduce more automation. Many labor-intensive tasks, such as preparing and labeling data that involve repetitive, tedious, and extremely time-consuming functions, will begin to be automated in 2022 so AI developers can focus on perfecting algorithms instead of data preparation and orchestrating compute and cloud resources.
What’s the main driving force pushing the data science industry? How are things changing in 2022?
Leah: There will be more business users and citizen developers.
In New Year 2022, there will be more off-the-shelf technology that will be used by subject matter experts such as product managers, actuaries, and risk managers. No-code machine learning will make data-flows available for simple data analysis projects like predicting retail profits and implementing dynamic pricing.
What role do you foresee for women leaders in AI in 2022?
Leah: Women executives will rise up the ranks.
There has been a global push to involve more women in science and technology careers and AI is one of the fields in which women can experience tremendous success. This move of women to AI is not only critical for the advancement of women, but it will also ensure that the models themselves show diversity.
What are your predictions for the Computing and Cloud management service providers?
Leah: Compute and Cloud Resources will be called upon the fly.
AI developers will have the ability to choose the best of breed compute and cloud solution per machine learning model on the fly, to prevent vendor lock-in while also giving them the luxury to try new innovative technologies without risking their whole AI/ML environment. The ability to choose different cloud storage vendors, as well as CPUs, GPUs, and specialized AI chips will accelerate innovation, limit risk, and speed up time to market, while lowering the overall cost of AI.
So, embedded AI would become more mainstream in the coming months?
Leah: Of course, yes! AI will be more embedded.
In the coming year, we will also see AI applications at the forefront of enterprise and even government strategies where it becomes the driving force for more business decisions transparent running behind the scenes. In addition, more products and services will have AI built-in, where AI is embedded in the core of everything from architecture to operations.
As the new online economy demands more data for companies to be more efficient and provide a better customer experience, there will be more enabling technologies available to ease the transition to an AI economy where companies can learn faster how to be better.