How data and AI are driving opportunities for LinkedIn – and its members and customers

We're excited to bring Transform 2022 back in person on July 19 and virtually from July 20-28. Join leaders in AI and data for in-depth discussions and exciting networking opportunities. Sign up today!

Despite its vast network of more than 750 million members, job-focused social media giant, LinkedIn chief data officer Ya Xu distills the role of artificial intelligence (AI) and data in the company in three categories: talent, knowledge and product.

Wherever data or AI is applied, Xu says LinkedIn ultimately aims to approach everything in a way that "creates economic opportunity and value for members, customers and businesses".

But how is the networking giant tackling key issues like bias while innovating for the future? How does it protect privacy, while providing its wealth of useful data to inform research?

Behind the AI ​​that powers modern networks

As the field of AI continues to evolve, conversations among industry professionals continue to evolve with it, perhaps as a way to empower the technology and its developers.

Event

Transform 2022

Join us at the leading Applied AI event for enterprise business and technology decision makers on July 19 and virtually July 20-28.

register here

Threads and posts about AI bias, susceptibility and its opportunities are plentiful on Twitter and, of course, on LinkedIn as well. These conversations are often about the impact of AI on the use and experience of social platforms themselves.

At VentureBeat's Transform 2022 Data and AI Executive Summit, conversations further underscored these trends.

LinkedIn is uniquely positioned both as a developer and deployer of its own AI models and as a researcher with its spectrum of data collection. It is also a platform at the heart of professional relations, promoting a space for dialogue on the challenges and developments in the industry.

Xu said that because LinkedIn aims to provide economic opportunity to every member, the company "simply cannot afford to not do AI responsibly." .

LinkedIn embeds responsible AI across its enterprise, with checks and balances in place that measure and aim to detect any unintended consequences or biased outcomes from the models that drive enterprise AI. It's important, Xu said, that teams interacting with any part of AI algorithms need to plan together, meet and communicate effectively. This, especially in a large enterprise, helps provide another way to keep the AI ​​"under control".

For example, Xu said that if a recruiter searches LinkedIn's platform for "nurses" or "data scientists," his team works hard to ensure responsible results are shown. , which means that the algorithm does not generate more female results. for the nursing profession or a disproportionate number of men for data scientist search results. Xu noted that regardless of whether a LinkedIn member is taking advantage of learning features, applying for jobs, building relationships, or researching potential candidates for recruitment, AI should always be developed keeping in mind. mind the end-user interactions.

"He has b...