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AiThority Interview Series With Anant Joshi, CRO at Factmata

Anant Joshi

Advertising technology is one of my main passions. I am the CRO of Factmata, where my current focus is business development.


We are a London based startup developing a cutting-edge community-driven AI Brand Safety solution for advertisers. Our goal is to reduce misinformation and abusive content on the internet.

Tell us about your journey into Artificial Intelligence? How exciting is it for you to be a part of an AI-driven media platform?

I’ve worked in online advertising for 18 years and have seen many new technologies emerge that have changed the way we work for the better. Today, media buyers and sellers use technology platforms such as supply-side platforms (SSPs), demand-side platforms (DSPs), ad exchanges, data management platforms (DMPs) and customer data platforms (CDPs) to buy and sell media in the most efficient way possible. The smarter we get at buying and selling online advertising, the faster the industry will grow

Artificial intelligence (AI) is the latest development that is revolutionizing the way the online advertising ecosystem works so it’s really exciting for me to be at the forefront of this opportunity. One of the reasons AI is good for media buyers and sellers is that it increases the scale at which things like data analysis can be done. This is extremely important because it allows them to react to changes in real time and capture every opportunity to fine tune their marketing efforts. The insights that come out of AI platforms and the time saved by automating back-end processes can then be used to do more strategic, creative, things and improve the way brands and publishers engage with consumers.

What are the core tenets of your AI roadmap?

Our mission at Factmata is to protect people, advertisers, publishers and other businesses from deceptive or misleading content online. To do this we’re investing in people who are leading experts in natural language understanding (NLU) and AI and feeding as much information as possible into our algorithms so they evolve and scale with the pace of change in the online advertising ecosystem.

In parallel, we’re planning to launch our new platform, called Briefr, which will allow journalists and domain experts to annotate articles and post them on our platform. Briefr works by gathering the data from these annotations and scoring the credibility and trustworthiness of that content. This means that instead of news being shared on likes, it will be shared based on credibility and trustworthiness of that content. The data that Briefr captures will also be fed into our algorithms to help our AI to learn faster and make better decisions based on human input.

It’s this blend of approaches that sets us apart from the rest of the market.

What are your predictions for AI in Programmatic? How do you intend to expand your horizon to meet media revenue objectives and automation standards?

There’s a lot of hype about AI in programmatic advertising and many companies claim their technology has AI capabilities when it doesn’t. Media buyers and sellers are becoming savvier about the smoke and mirrors presented by some companies and are demanding to know more about the AI capabilities of technology before investing. This will separate the wheat from the chaff and allow the AI industry to flourish based on trust and understanding.

I think we will see AI being applied throughout the supply chain to better understand the value of an impression for both a publisher and a brand and create a marketplace where the price paid for online ads is fair for both the publisher and the advertiser based on where the ad will be shown and to who.

We’re not planning to expand into media buying or selling. We’re not in the business of telling people what they should do, we’re here to give people the information they need to make informed decisions. Armed with this information, brands will be able to run more effective, brand safe campaigns based on the level of risk they are willing to take to reach their goals.

One of the problems we see in the market today is that existing brand safety technology works by blacklisting entire domains which drastically reduces the reach of campaigns. If you reduce the reach of a campaign you’re going to see a fall in performance metrics. We don’t do this, we identify individual pages that contain misinformation and warn advertisers that they might not want to advertise on those specific pages. This allows brands to run brand safe campaigns without throttling reach. If we’re successful we could help drive a boost in programmatic ad spending.

When it comes to automation standards, we want to lead the way and establish best practices and educate the market. Our technology is unique so we’re in a good position to do this.

How can AI/machine learning help to build a brand-safe media ecosystem?

Traditional brand safety technology works on rules-based systems whereby the technology reads the content on a webpage looking at each keyword and identifies the page as safe or not safe based on the individual words. Factmata’s AI is able to not only identify the keywords on a page but to read whole sentences and understand the context in which those words are being used.

For example, a home furnishings brand may not want their ads to appear on religious websites, so they might use a brand safety technology to screen out any web pages that contain the word “Buddha”. This would rule out any homestyle content that references a Buddha statue in the context of home decoration. Our AI would read the whole sentence on the homestyle website and flag it as potentially unsafe, but with a score that indicates the level of risk of exposing a brand to an unsafe environment. In this case, it might be 1 out of 100.

It’s these quality scores that enable brands to set their own tolerances in different areas e.g. fake news, politically extreme content etc. By allowing brands to take control of limiting where their ads are shown we are cutting off revenue to those who create misinformation online as for most of them their only source of revenue is online advertising. This is how we’re cleaning up the ecosystem, we’re not censoring content, we’re putting brands in control.

How do you consume all the information on AI and other emerging technologies for advertising and branding?

I like to stay informed by reading case studies, going to events about AI and/or advertising and listening to podcasts which are a great way to discover new ideas.

In 2018-2020, what are the biggest challenges in the adoption of AI/ML? How do you see the media intelligence market evolving in its fight against Fake News and extremist content?

There’s still a lot of education to be done around the capabilities of brand safety AI. One of the biggest challenges is that moving away from existing technologies in a stack is hard to do and poses a risk to performance if it goes wrong. That’s why it’s hard for emerging companies to enter the market because you need a really strong product to be able to disrupt something which on the surface appears to be working well.

When it comes to fake news and extremist content, AI is the only option because it’s not possible for any rules-based or human solution to cope with the sheer volume of content online and the pace at which new content is created.

How do you make AI deliver economic benefits as well as social goodwill?

AI allows people to do things better, faster and at lower costs. Contrary to popular opinion AI doesn’t replace humans – rather it allows them to do more.

A study by PwC predicts that the application of AI has the potential to double economic growth rates in those economies over the next couple of decades by application of AI, and a key reason for that is by improving human productivity by up to 40 percent in the way that they do their work.

Here’s a simple example of how AI can be used to increase productivity and profitability for a retailer. By applying AI to automate back-end processes and data analysis retailers can make optimize stock levels based on the amount of warehouse space available, production time, and sales trends. Having optimal stock levels means more sales and less wastage.

Tell us about your Research programs and the most outstanding digital campaign at Factmata?

A number of pilot tests are underway right now and we’re able to demonstrate the kind of sites and content that are going unnoticed. We’ve proved that our technology works and that it helps brands avoid having their ads displayed in the wrong places.

What is your vision in making Programmatic technologies and AI readily available to local marketing communities?

We need to make sure that any technology is cost-effective and drives business goals. This means really understanding people’s business goals and building a technology that is able to meet short term and long term objectives and adapt to changes in the marketplace.

At the moment, I’m talking to as many people as I can about the challenges they face and the issues they are experiencing trying to solve those challenges. I’m passionate about making technology accessible so I’m also working to educate people about what AI is (and is not) and how it can be applied to marketing and the benefits.

What AI start-ups and labs are you keenly following?

This year, I decided to embrace a vegan diet and started to look into innovative plant-based food production. I discovered a company called ‘The Not Company’ shortened to  ‘NotCo’ that combines AI with food-science to craft cutting-edge plant-based foods. So any companies that focus on impact to climate change and agriculture interest me. Bowery farming seems to be tackling agriculture in a completely new way, which will have huge benefits for humans and the environment. They have a small number of crops at the moment, but it will be interesting to watch the company grow and diversify.

What technologies within AI and computing are you interested in?

I’m interested in AI for good where there are clear benefits for society, and where human input is seen as essential in monitoring the technology. There are innovative AI startups such as Arterys, aiming to reduce the time needed to provide accurate medical diagnoses.

As an AI leader, what industries you think would be fastest to adopting AI/ML with smooth efficiency? What are the new emerging markets for AI technology markets?

The greatest economic gains from AI will be in China (26% boost to GDP in 2030) and North America (14.5% boost), equivalent to a total of $10.7 trillion and accounting for almost 70% of the global economic impact, according to research by PwC.

Other than advertising, the legal, finance and healthcare industries have a lot to gain from AI. When looking at indicators that an industry or company will benefit from AI you need to look at several things:

  1. Ratio of junior staff to senior staff – the more junior staff there are, the greater the potential for AI
  2. Data – the greater a business’s data pool is the more likely it is that AI can drive value because of its ability to process huge amounts of data in a fraction of the time it would take a human
  3. The number of variables that impact business performance – the more influences there are on a business the harder it is to predict the impact of change. AI can model different scenarios and change the models in real time as markets shift

What’s your smartest work related shortcut or productivity hack?

Slack is brilliant for cutting down on emails and communicating with everyone in a team quickly. The biggest time saving for me comes through being able to share documents and thoughts without getting lost in long email chains. We also use Streak CRM and Airtable for keeping track of our projects.

Tag the one person in the industry whose answers to these questions you would love to read:

Matias Muchnick – CEO & Founder at NotCo

Thank you Anant! That was fun and hope to see you back on AiThority soon.

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