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Tiger Global and Ant Financial lead $500M investment in China’s shared housing startup Danke

Posted by on Mar 1, 2019 in affordable housing, alibaba, Ant Financial, apartment, Asia, Baidu, Beijing, business intelligence, China, danke apartment, jack ma, LinkedIn, major, property, Real Estate, renting, Tiger Global Management, WeWork, Xi Jinping | 0 comments

A Chinese startup that’s taking a dorm-like approach to urban housing just raised $500 million as its valuation jumped over $2 billion. Danke Apartment, whose name means “eggshell” in Chinese, closed the Series C round led by returning investor Tiger Global Management and newcomer Ant Financial, Alibaba’s e-payment and financial affiliate controlled by Jack Ma.

Four years ago, Beijing-based Danke set out with a mission to provide more affordable housing for young Chinese working in large urban centers. It applies the coworking concept to housing by renting apartments that come renovated and fully furnished, a model not unlike that of WeWork’s WeLive. The idea is by slicing up a flat designed for a family of three to four — the more common type of urban housing in China — into smaller units, young professionals can afford to live in nicer neighborhoods as Danke takes care of hassles like housekeeping and maintenance. To date, the startup has set foot in ten major Chinese cities.

With the new funds, Danke plans to upgrade its data processing system that deals with rental transactions. Housing prices are set by AI-driven algorithms that take into account market forces such as locations rather than rely on the hunches of a real estate agent. The more data it gleans, the smarter the system becomes. That layout is the engine of the startup, which believes an internet platform play is a win-win for both homeowners and tenants because it provides greater transparency and efficiency while allowing the company to scale faster.

“We are focused on business intelligence from day one,” Danke’s angel investor and chairman Derek Shen told TechCrunch in an interview. Shen was the former president of LinkedIn China and was instrumental in helping the professional networking site enter the country. “By doing so we are eliminating the need to set up offline retail outlets and are able to speed up the decision-making process. What landlords normally care is who will be the first to rent out their property. The model is also copiable because it requires less manpower.”

“We’ve proven that the rental housing business can be decentralized and done online,” added Shen.

danke apartment

Photo: Danke Apartment via Weibo

Danke doesn’t just want to digitize the market it’s after. Half of the company’s core members have hailed from Nuomi, the local services startup that Shen founded and was sold to Baidu for $3.2 billion back in 2015. Having worked for a business of which mission was to let users explore and hire offline services from their connected devices, these executives developed a propensity to digitize all business aspects including Danke’s day-to-day operations, a scheme that will also take up some of the new funds. This will allow Danke to “boost operational efficiency and cut costs” as it “actively works with the government to stabilize rental prices in the housing market,” the company says.

The rest of the proceeds will go towards improving the quality of Danke’s apartment amenities and tenant experiences, a segment that Shen believes will see great revenue potential down the road, akin to how WeWork touts software services to enterprises. The money will also enable Danke, which currently zeroes in on office workers and recent college graduates, to explore the emerging housing market for blue-collar workers.

Other investors from the round include new backer Primavera Capital and existing investors CMC Capital, Gaorong Capital and Joy Capital.

China’s rental housing market has boomed in recent years as Beijing pledges to promote affordable apartments in a country where few have the money to buy property. As President Xi Jinping often stresses, “houses are for living in, not for speculation.” As such, investors and entrepreneurs have been piling into the rental flat market, but that fervor has also created unexpected risks.

One much-criticized byproduct is the development of so-called “rental loans.” It goes like this: Housing operators would obtain loans in tenants’ names from banks or other lending institutions allegedly by obscuring relevant details from contracts. So when a tenant signs an agreement that they think binds them to rents, they have in fact agreed to take on loans and their “rent” payments become monthly loan repayments.

Housing operators are keen to embrace such practices for the loans provide working capital for renovation and their pipeline of properties. On the other hand, the capital allows companies like Danke to lower deposits for cash-strapped young tenants. “There’s nothing wrong with the financial instrument itself,” suggested Shen. “The real issue is when the housing operator struggles to repay, so the key is to make sure the business is well-functioning.”

Danke alongside competitors Ziroom and 5I5J has drawn fire for not fully informing tenants when signing contracts. Shen said his company is actively working to increase transparency. “We will make it clear to customers that what they are signing are loans. As long as we give them enough notice, there should be little risk involved.”


Source: The Tech Crunch

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Facebook warned over privacy risks of merging messaging platforms

Posted by on Feb 2, 2019 in antitrust, Apps, Brian Acton, business intelligence, data protection, e2e encryption, Europe, European Commission, Facebook, GDPR, General Data Protection Regulation, instagram, Ireland, Mark Zuckerberg, messaging apps, Privacy, Social, Social Media, WhatsApp | 0 comments

Facebook’s lead data protection regulator in Europe has asked the company for an “urgent briefing” regarding plans to integrate the underlying infrastructure of its three social messaging platforms.

In a statement posted to its website late last week the Irish Data Protection Commission writes: “Previous proposals to share data between Facebook companies have given rise to significant data protection concerns and the Irish DPC will be seeking early assurances that all such concerns will be fully taken into account by Facebook in further developing this proposal.”

Last week the New York Times broke the news that Facebook intends to unify the backend infrastructure of its three separate products, couching it as Facebook founder Mark Zuckerberg asserting control over acquisitions whose founders have since left the building.

Instagram founders, Kevin Systrom and Mike Krieger, left Facebook last year, as a result of rising tensions over reduced independence, according to our sources.

While WhatsApp’s founders left Facebook earlier, with Brian Acton departing in late 2017 and Jan Koum sticking it out until spring 2018. The pair reportedly clashed with Facebook execs over user privacy and differences over how to monetize the end-to-end encrypted platform.

Acton later said Facebook had coached him to tell European regulators assessing whether to approve the 2014 merger that it would be “really difficult” for the company to combine WhatsApp and Facebook user data.

In the event, Facebook went on to link accounts across the two platforms just two years after the acquisition closed. It was later hit with a $122M penalty from the European Commission for providing “incorrect or misleading” information at the time of the merger. Though Facebook claimed it had made unintentional “errors” in the 2014 filing.

A further couple of years on and Facebook has now graduated to seeking full platform unification of separate messaging products.

“We want to build the best messaging experiences we can; and people want messaging to be fast, simple, reliable and private,” a spokesperson told us when we asked for a response to the NYT report. “We’re working on making more of our messaging products end-to-end encrypted and considering ways to make it easier to reach friends and family across networks.”

“As you would expect, there is a lot of discussion and debate as we begin the long process of figuring out all the details of how this will work,” the spokesperson added, confirming the substance of the NYT report.

There certainly would be a lot of detail to be worked out. Not least the feasibility of legally merging user data across distinct products in Europe, where a controversial 2016 privacy u-turn by WhatsApp — when it suddenly announced it would after all share user data with parent company Facebook (despite previously saying it would never do so), including sharing data for marketing purposes — triggered swift regulatory intervention.

Facebook was forced to suspend marketing-related data flows in Europe. Though it has continued sharing data between WhatsApp and Facebook for security and business intelligence purposes, leading to the French data watchdog to issue a formal notice at the end of 2017 warning the latter transfers also lack a legal basis.

A court in Hamburg, Germany, also officially banned Facebook from using WhatsApp user data for its own purposes.

Early last year, following an investigation into the data-sharing u-turn, the UK’s data watchdog obtained an undertaking from WhatsApp that it would not share personal data with Facebook until the two services could do so in a way that’s compliant with the region’s strict privacy framework, the General Data Protection Regulation (GDPR).

Facebook only avoided a fine from the UK regulator because it froze data flows after the regulatory intervention. But the company clearly remains on watch — and any fresh moves to further integrate the platforms would trigger instant scrutiny, evidenced by the shot across the bows from the DPC in Ireland (Facebook’s international HQ is based in the country).

The 2016 WhatsApp-Facebook privacy u-turn also occurred prior to Europe’s GDPR coming into force. And the updated privacy framework includes a regime of substantially larger maximum fines for any violations.

Under the regulation watchdogs also have the power to ban companies from processing data. Which, in the case of a revenue-rich data-mining giant like Facebook, could be a far more potent disincentive than even a billion dollar fine.

We’ve reached out to Facebook for comment on the Irish DPC’s statement and will update this report with any response.

Here’s the full statement from the Irish watchdog:

While we understand that Facebook’s proposal to integrate the Facebook, WhatsApp and Instagram platforms is at a very early conceptual stage of development, the Irish DPC has asked Facebook Ireland for an urgent briefing on what is being proposed. The Irish DPC will be very closely scrutinising Facebook’s plans as they develop, particularly insofar as they involve the sharing and merging of personal data between different Facebook companies. Previous proposals to share data between Facebook companies have given rise to significant data protection concerns and the Irish DPC will be seeking early assurances that all such concerns will be fully taken into account by Facebook in further developing this proposal. It must be emphasised that ultimately the proposed integration can only occur in the EU if it is capable of meeting all of the requirements of the GDPR.

Facebook may be hoping that extending end-to-end encryption to Instagram as part of its planned integration effort, per the NYT report, could offer a technical route to stop any privacy regulators’ hammers from falling.

Though use of e2e encryption still does not shield metadata from being harvested. And metadata offers a rich source of inferences about individuals which, under EU law, would certainly constitute personal data. So even with robust encryption across the board of Instagram, Facebook and WhatsApp the unified messaging platforms could still collectively leak plenty of personal data to their data-mining parent.

Facebook’s apps are also not open source. So even WhatsApp, which uses the respected Signal Protocol for its e2e encryption, remains under its control — with no ability for external audits to verify exactly what happens to data inside the app (such as checking what data gets sent back to Facebook). Users still have to trust Facebook’s implementation but regulators might demand actual proof of bona fide messaging privacy.

Nonetheless, the push by Facebook to integrate separate messaging products onto a single unified platform could be a defensive strategy — intended to throw dust in the face of antitrust regulators as political scrutiny of its market position and power continues to crank up. Though it would certainly be an aggressive defence to more tightly knit separate platforms together.

But if the risk Facebook is trying to shrink is being forced, by competition regulators, to sell off one or two of its messaging platforms it may feel it has nothing to lose by making it technically harder to break its business apart.

At the time of the acquisitions of Instagram and WhatsApp Facebook promised autonomy to their founders. Zuckerberg has since changed his view, according to the NYT — believing integrating all three will increase the utility of each and thus provide a disincentive for users to abandon each service.

It may also be a hedge against any one of the three messaging platforms decreasing in popularity by furnishing the business with internal levers it can throw to try to artifically juice activity across a less popular app by encouraging cross-platform usage.

And given the staggering size of the Facebook messaging empire, which globally sprawls to 2.5BN+ humans, user resistance to centralized manipulation via having their buttons pushed to increase cross-platform engagement across Facebook’s business may be futile without regulatory intervention.


Source: The Tech Crunch

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Japan’s Sansan raises $26.5M to help Southeast Asia get more from business cards

Posted by on Dec 6, 2018 in Asia, business intelligence, computing, customer relationship management, dcm ventures, Europe, Facebook, funding, Fundings & Exits, India, LinkedIn, recruitment, Sansan, sbi investment, Singapore, Social Media, social network, Software, Southeast Asia, t.rowe price, United States, world wide web | 0 comments

The humble business card is a target for disruption in Southeast Asia after Japanese contacts management startup Sansan raised JPY 3 billion ($26.5 million) to expand its business into the region.

Founded way back in 2007, Sansan helps bring business intelligence to companies through a system that helps build connections between users and both internal employees and external contacts using, among other things, business cards.

“Our purpose is to use tech to enhance the utility and value of business cards,” Sansan co-founder and director Kei Tomioka told TechCrunch in an interview. “They are customary for business in most parts of the world, esJapanlly japan, but there’s no easy way to digitize them.”

This new round will bring that focus to Southeast Asia, where Sansan already has an office in Singapore. The capital — which is a Series E round — was provided Japan Post Capital, T. Rowe Price, SBI Investment and DCM Ventures, and it takes Sansan to around $100 million raised to date.

Sansan claims that 7,000 corporations use its core product — also called Sansan — which helps build and organize networks. At its core, users scan another person’s business card which is then digitized, uploaded to the cloud and made part of their database. The Sansan system then allows interactions, such as meetings, calls, notes and more to be added to the entry to help track interactions. The resources are held within companies, rather than employees themselves, which means strategies around sales, marketing and more can be kept organized and centralized.

In addition, Sansan operates a LinkedIn -like service called Eight which is available for free and is linked to the core product, allowing users to update their job, company, etc without having to provide a new business card. Eight has some two million users today, according to Sansan.

Unlike LinkedIn, however, which is commonly used for finding jobs, Tomioka suggested that Eight and Sansan help maintain networks and increase communication and engagement.

Sansan CEO Chikahiro Terada started the business in 2006 alongside fellow co-founders Kei Tomioka, Joraku Satoru, Kenji Shiomi and Motohisa Tsunokawa

Tomioka — who previously worked for Oracle in Thailand — said that he sees much potential for the services in Southeast Asia, where the region’s digital economy is expected to triple by 2025, albeit with a greater focus on SMEs rather than Japan-style mega corporations.

Already, Sansan has picked up some 100 or so clients in the region — mostly by targeting Japanese corporations in Singapore — while Eight has reached 100,000 registered users across Southeast Asia since a soft launch in October 2017.

“We want to expand to globally and Singapore is our first step,” said Tomioka, indicating that there are future plans to look at business in India, Europe and potentially the U.S. further down the line. Elsewhere, the firm is hiring data scientists as it aims to bring additional smarts to its services.

The proposition is interesting — personally speaking I have multiple stacks of business cards sitting idle — but it remains to be seen how open businesses in Southeast Asia will be to paying for the service, even with clear benefits. Saas as a model is still establishing its roots among SMEs while there are already popular options. LinkedIn is, of course, the de facto professional social network while Facebook, which has been ramping up its efforts in that space lately, is also a popular option.

Update: The original version of this article was updated to reflect that quoted comments were from Sansan co-founder Kei Tomioka not Chikahiro Terada.


Source: The Tech Crunch

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Integrate.ai pulls in $30M to help businesses make better customer-centric decisions

Posted by on Sep 12, 2018 in Advertising Tech, Artificial Intelligence, bias, business intelligence, Canada, deep learning, ethics, Facebook, fairness, Fundings & Exits, Georgian Partners, InfoSum, Integrate.ai, machine learning, Portag3 Ventures, Privacy, Real Ventures, SaaS, social web, TC, toronto | 3 comments

Helping businesses bring more firepower to the fight against AI-fuelled disruptors is the name of the game for Integrate.ai, a Canadian startup that’s announcing a $30M Series A today.

The round is led by Portag3 Ventures . Other VCs include Georgian Partners, Real Ventures, plus other (unnamed) individual investors also participating. The funding will be used for a big push in the U.S. market.

Integrate.ai’s early focus has been on retail banking, retail and telcos, says founder Steve Irvine, along with some startups which have data but aren’t necessarily awash with AI expertise to throw at it. (Not least because tech giants continue to hoover up talent.)

Its SaaS platform targets consumer-centric businesses — offering to plug paying customers into a range of AI technologies and techniques to optimize their decision-making so they can respond more savvily to their customers. Aka turning “high volume consumer funnels” into “flywheels”, if that’s a mental image that works for you.

In short it’s selling AI pattern spotting insights as a service via a “cloud-based AI intelligence platform” — helping businesses move from “largely rules-based decisioning” to “more machine learning-based decisioning boosted by this trusted signals exchange of data”, as he puts it.

Irvine gives the example of a large insurance aggregator the startup is working with to optimize the distribution of gift cards and incentive discounts to potential customers — with the aim of maximizing conversions.

“Obviously they’ve got a finite amount of budget for those — they need to find a way to be able to best deploy those… And the challenge that they have is they don’t have a lot of information on people as they start through this funnel — and so they have what is a classic ‘cold start’ problem in machine learning. And they have a tough time allocating those resources most effectively.”

“One of the things that we’ve been able to help them with is to, essentially, find the likelihood of those people to be able to convert earlier by being able to bring in some interesting new signal for them,” he continues. “Which allows them to not focus a lot of their revenue or a lot of those incentives on people who either have a low likelihood of conversion or are most likely to convert. And they can direct all of those resources at the people in the middle of the distribution — where that type of a nudge, that discount, might be the difference between them converting or not.”

He says feedback from early customers suggests the approach has boosted profitability by around 30% on average for targeted business areas — so the pitch is businesses are easily seeing the SaaS easily paying for itself. (In the cited case of the insurer, he says they saw a 23% boost in performance — against what he couches as already “a pretty optimized funnel”.)

“We find pretty consistent [results] across a lot of the companies that we’re working with,” he adds. “Most of these decisions today are made by a CRM system or some other more deterministic software system that tends to over attribute people that are already going to convert. So if you can do a better job of understanding people’s behaviour earlier you can do a better job at directing those resources in a way that’s going to drive up conversion.”

The former Facebook marketing exec, who between 2014 and 2017 ran a couple of global marketing partner programs at Facebook and Instagram, left the social network at the start of last year to found the business — raising $9.6M in seed funding in two tranches, according to Crunchbase.

The eighteen-month-old Toronto based AI startup now touts itself as one of the fastest growing companies in Canadian history, with a headcount of around 40 at this point, and a plan to grow staff 3x to 4x over the next 12 months. Irvine is also targeting growing revenue 10x, with the new funding in place — gunning to carve out a leadership position in the North American market.

One key aspect of Integrate.ai’s platform approach means its customers aren’t only being helped to extract more and better intel from their own data holdings, via processes such as structuring the data for AI processing (though Irvine says it’s also doing that).

The idea is they also benefit from the wider network, deriving relevant insights across Integrate.ai’s pooled base of customers — in a way that does not trample over privacy in the process. At least, that’s the claim.

(It’s worth noting Integrate.ai’s network is not a huge one yet, with customers numbering in the “tens” at this point — the platform only launched in alpha around 12 months ago and remains in beta now. Named customers include the likes of Telus, Scotiabank, and Corus.)

So the idea is to offer an alternative route to boost business intelligence vs the “traditional” route of data-sharing by simply expanding databases — because, as Irvine points out, literal data pooling is “coming under fire right now — because it is not in the best interests, necessarily, of consumers; there’s some big privacy concerns; there’s a lot of security risk which we’re seeing show up”.

What exactly is Integrate.ai doing with the data then? Irvine says its Trusted Signals Exchange platform uses some “pretty advanced techniques in deep learning and other areas of machine learning to be able to transfer signals or insights that we can gain from different companies such that all the companies on our platform can benefit by delivering more personalized, relevant experiences”.

“But we don’t need to ever, kind of, connect data in a more traditional way,” he also claims. “Or pull personally identifiable information to be able to enable it. So it becomes very privacy-safe and secure for consumers which we think is really important.”

He further couches the approach as “pretty unique”, adding it “wouldn’t even have been possible probably a couple of years ago”.

From Irvine’s description the approach sounds similar to the data linking (via mathematical modelling) route being pursued by another startup, UK-based InfoSum — which has built a platform that extracts insights from linked customer databases while holding the actual data in separate silos. (And InfoSum, which was founded in 2016, also has a founder with a behind-the-scenes’ view on the inners workings of the social web — in the form of Datasift’s Nic Halstead.)

Facebook’s own custom audiences product, which lets advertisers upload and link their customer databases with the social network’s data holdings for marketing purposes is the likely inspiration behind all these scenes.

Irvine says he spotted the opportunity to build this line of business having been privy to a market overview in his role at Facebook, meeting with scores of companies in his marketing partner role and getting to hear high level concerns about competing with tech giants. He says the Facebook job also afforded him an overview on startup innovation — and there he spied a gap for Integrate.ai to plug in.

“My team was in 22 offices around the world, and all the major tech hubs, and so we got a chance to see any of the interesting startups that were getting traction pretty quickly,” he tells TechCrunch. “That allowed us to see the gaps that existed in the market. And the biggest gap that I saw… was these big consumer enterprises needed a way to use the power of AI and needed access to third party data signals or insights to be able to enabled them to transition to this more customer-centric operating model to have any hope of competing with the large digital disruptors like Amazon.

“That was kind of the push to get me out of Facebook, back from California to Toronto, Canada, to start this company.”

Again on the privacy front, Irvine is a bit coy about going into exact details about the approach. But is unequivocal and emphatic about how ad tech players are stepping over the line — having seen into that pandora’s box for years — so his rational to want to do things differently at least looks clear.

“A lot of the techniques that we’re using are in the field of deep learning and transfer learning,” he says. “If you think about the ultimate consumer of this data-sharing, that is insight sharing, it is at the end these AI systems or models. Meaning that it doesn’t need to be legible to people as an output — all we’re really trying to do is increase the map; make a better probabilistic decision in these circumstances where we might have little data or not the right data that we need to be able to make the right decision. So we’re applying some of the newer techniques in those areas to be able to essentially kind of abstract away from some of the more sensitive areas, create representations of people and patterns that we see between businesses and individuals, and then use that as a way to deliver a more personalized predictions — without ever having to know the individual’s personally identifiable information.”

“We do do some work with differential privacy,” he adds when pressed further on the specific techniques being used. “There’s some other areas that are just a little bit more sensitive in terms of the work that we’re doing — but a lot of work around representative learning and transfer learning.”

Integrate.ai has published a whitepaper — for a framework to “operationalize ethics in machine learning systems” — and Irvine says it’s been called in to meet and “share perspectives” with regulators based on that.

“I think we’re very GDPR-friendly based on the way that we have thought through and constructed the platform,” he also says when asked whether the approach would be compliant with the European Union’s tough new privacy framework (which also places some restrictions on entirely automated decisions when they could have a significant impact on individuals).

“I think you’ll see GDPR and other regulations like that push more towards these type of privacy preserving platforms,” he adds. “And hopefully away from a lot of the really creepy, weird stuff that is happening out there with consumer data that I think we all hope gets eradicated.”

For the record, Irvine denies any suggestion that he was thinking of his old employer when he referred to “creepy, weird stuff” done with people’s data — saying: “No, no, no!”

“What I did observe when I was there in ad tech in general, I think if you look at that landscape, I think there are many, many… worse examples of what is happening out there with data than I think the ones that we’re seeing covered in the press. And I think as the light shines on more of that ecosystem of players, I think we will start to see that the ways they’ve thought about data, about collection, permissioning, usage, I think will change drastically,” he adds.

“And the technology is there to be able to do it in a much more effective way without having to compromise results in too big a way. And I really hope that that sea change has already started — and I hope that it continues at a much more rapid pace than we’ve seen.”

But while privacy concerns might be reduced by the use of an alternative to traditional data-pooling, depending on the exact techniques being used, additional ethical considerations are clearly being dialled sharply into view if companies are seeking to supercharge their profits by automating decision making in sensitive and impactful areas such as discounts (meaning some users stand to gain more than others).

The point is an AI system that’s expert at spotting the lowest hanging fruit (in conversion terms) could start selectively distributing discounts to a narrow sub-section of users only — meaning other people might never even be offered discounts.

In short, it risks the platform creating unfair and/or biased outcomes.

Integrate.ai has recognized the ethical pitfalls, and appears to be trying to get ahead of them — hence its aforementioned ‘Responsible AI in Consumer Enterprise’ whitepaper.

Irvine also says that raising awareness around issues of bias and “ethical AI” — and promoting “more responsible use and implementation” of its platform is another priority over the next twelve months.

“The biggest concern is the unethical treatment of people in a lot of common, day-to-day decisions that companies are going to be making,” he says of problems attached to AI. “And they’re going to do it without understanding, and probably without bad intent, but the reality is the results will be the same — which is perpetuating a lot of biases and stereotypes of the past. Which would be really unfortunate.

“So hopefully we can continue to carve out a name, on that front, and shift the industry more to practices that we think are consistent with the world that we want to live in vs the one we might get stuck in.”

The whitepaper was produced by a dedicated internal team, which he says focuses on AI ethics and fairness issues, and is headed up by VP of product & strategy, Kathryn Hume.

“We’re doing a lot of research now with the Vector Institute for AI… on fairness in our AI models, because what we’ve seen so far is that — if left unattended, if all we did was run these models and not adjust for some of the ethical considerations — we would just perpetuate biases that we’ve seen in the historical data,” he adds.

“We would pick up patterns that are more commonly associated with maybe reinforcing particular stereotypes… so we’re putting a really dedicated effort — probably abnormally large, given our size and stage — towards leading in this space, and making sure that that’s not the outcome that gets delivered through effective use of a platform like ours. But actually, hopefully, the total opposite: You have a better understanding of where those biases might creep in and they could be adjusted for in the models.”

Combating unfairness in this type of AI tool would mean a company having to optimize conversion performance a bit less than it otherwise could.

Though Irvine suggests that’s likely just in the short term. Over the longer term he argues you’re laying the foundations for greater growth — because you’re building a more inclusive business, saying: “We have this conversational a lot. “I think it’s good for business, it’s just the time horizon that you might think about.”

“We’ve got this window of time right now, that I think is a really precious window, where people are moving over from more deterministic software systems to these more probabilistic, AI-first platforms… They just operate much more effectively, and they learn much more effectively, so there will be a boost in performance no matter what. If we can get them moved over right off the bat onto a platform like ours that has more of an ethical safeguard, then they won’t notice a drop off in performance — because it’ll actually be better performance. Even if it’s not optimized fully for short term profitability,” he adds.

“And we think, over the long term it’s just better business if you’re socially conscious, ethical company. We think, over time, especially this new generation of consumers, they start to look out for those things more… So we really hope that we’re on the right side of this.”

He also suggests that the wider visibility afforded by having AI doing the probabilistic pattern spotting (vs just using a set of rules) could even help companies identify unfairnesses they don’t even realize might be holding their businesses back.

“We talk a lot about this concept of mutual lifetime value — which is how do we start to pull in the signals that show that people are getting value in being treated well, and can we use those signals as part of the optimization. And maybe you don’t have all the signal you need on that front, and that’s where being able to access a broader pool can actually start to highlight those biases more.”


Source: The Tech Crunch

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