Enterprise

Why eBay’s AI chief is setting guardrails for use of low-code AI

Companies shouldn’t treat AI tools like regular software, according to eBay’s chief AI officer, Nitzan Mekel-Bobrov. They require special monitoring and permissions.

Why eBay’s AI chief is setting guardrails for use of low-code AI

What does it mean to be an "AI-first" company?

Illustration: Protocol

Ebay’s Nitzan Mekel-Bobrov has big plans for helping the ecommerce mainstay evolve into what he calls an AI-first company. The December launch of eBay’s proprietary AI-based tech, which can generate 3D product views, is a sign of more immersive shopping and AI-enhanced customer communications to come, built using computer vision, natural language processing, streaming and computer graphics.

As eBay’s chief artificial intelligence officer, Mekel-Bobrov — who joined the company last year after helping lead AI engineering teams at Hearst, Capital One and most recently Booking.com — takes what he calls a distributed approach to disseminating AI across eBay. People in the company’s marketing science, advertising science, search science and buyer experience teams all have domain-specific strategies “but they’re also feeding into the broader enterprise-wide strategy around maturing our AI at eBay and becoming an AI-first company, which is not something any one domain can accomplish on its own,” Mekel-Bobrov told Protocol in an interview this week.

Nitzan Mekel-Bobrov, eBay's chief artificial intelligence officer, makes the rules.eBay

Still, Mekel-Bobrov guards against haphazardly building AI for customer use or incorporating AI-centric tools into workflows without parameters. It’s why he’s creating standards, best practices and governance for the use of low-code and no-code AI tech by others inside the company, and why he says AI requires a unique form of monitoring and maintenance that other software does not.

This interview has been edited and condensed for clarity.

Tell me about what a “distributed model” for AI technology use at eBay looks like, maybe in relation to the new 3D tech.

So that as a capability is something that we’re developing centrally, and then teams across different parts of the customer journey will be able to leverage that capability in an easy-to-deploy way. Our buyer experience team has deployed this on a number of our pages, a number of our portions of the customer journey, that they own. You’ll also see it in our eBay stores.

So far we’ve launched this for sneakers. If you look at some of our top sellers, they now feature 3D in their stores, in their digital storefront, which is owned by the eBay stores team. This is going to continue to roll out that way across multiple different areas.

It’s not just about eBay using AI to build experiences, but it’s actually about putting AI into the hands of our sellers and buyers, so that — especially our sellers — can build experiences for their buyers. It’s actually the sellers using our technology to build 3D experiences or 3D visualizations of their products.

Let's talk a little more about that – about people who usually don’t work with AI using it, or even building it. There are lots of low-code and no-code AI tools out there. Are non-engineers, people on the business side internally at eBay, using low-code AI or auto ML tools?

We are putting that into the hands of our developers in some instances where we felt that as long as they operated under certain parameters, under certain constraints, they could scale it up independently without in-depth knowledge of AI or machine learning. We are doing that first in areas that are low-risk, where there’s not really an opportunity for bias or privacy issues, et cetera, no fraud or cyber issues.

That’s where we started, and we’ll proceed, but we have to be very careful as we do this because we need to understand what’s being put into production in front of our customers, and as you scale that up, you need all of the instrumentation in place to be able to continuously monitor.

With AI, the piece of software could be performing correctly, but you need to monitor it because the world changes and it’s reacting to the world.

Are there processes in place to protect against risks when others at eBay use some of these third-party low-code AI technologies?

I am standing up essentially standards, best practices and governance that includes membership and representation from across the company in order to ensure that regardless of the implementation, the same standards are being kept and monitored. I think one of the biggest challenges, one of the big differences between an AI solution in production and other software: Software needs to be maintained and monitored in general, but engineers that deploy a piece of code, a general piece of software, their need to maintain it really has to do with technical performance issues. It’s about whether the actual integration is still up to date.

With AI, the piece of software could be performing correctly, but you need to monitor it because the world changes and it’s reacting to the world. And data changes, the performance of the model changes, therefore you have to monitor it on an ongoing basis. That’s something that a lot of companies misstep there, where they treat it like software without really treating it like an ongoing — I don’t want to say living — but it’s something that is continuously changing and evolving and needs to be monitored.

So as we allow teams across the company to use no-code or low-code, and any kind of AI development, we need to have the right requirements and processes in place for ongoing monitoring.

What’s planned for 2022 when it comes to hiring on the AI team or other AI trends?

We’re not one of those companies that goes out and just gobbles up every person with AI in their title; we’re strategic about it. But there are specific areas — for example, computer vision and natural language processing — that are of strategic importance for us this year and so we’re going to focus on those.

There’s been tremendous progress in our ability to understand language in the terms that customers communicate to us in, so I think for us what you’ll see in 2022, you’ll see further developments in our customer assistance or customer service conversational capabilities, but you’ll also see more multi-linguality.

We’re going to be really double-downing on immersive experiences. So, 3D was sort of an early foray but you’ll be seeing more products rolling out, especially on our mobile platform, to close the gap between ecommerce and physical retail to enable buyers to experience products in an immersive way so they have full confidence in their buying decision. That really comes through computer vision, natural language processing, through personalization as well as some adjacent technologies like streaming, like computer graphics.

Fintech

Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

Keep ReadingShow less
Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

Keep ReadingShow less
FTA
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.
Enterprise

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

It will be the second re:Invent with CEO Adam Selipsky as leader of the industry’s largest cloud provider after his return last year to AWS from data visualization company Tableau Software.

Keep ReadingShow less
Donna Goodison

Donna Goodison (@dgoodison) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

Keep ReadingShow less
Bennett Richardson

Bennett Richardson ( @bennettrich) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.

Enterprise

Why large enterprises struggle to find suitable platforms for MLops

As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

Keep ReadingShow less
Kate Kaye

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia.org and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

Latest Stories
Bulletins