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Never mind killer robots—here are six real AI dangers to watch out for in 2019

https://www.technologyreview.com/s/612689/never-mind-killer-robotshere-are-six-real-ai-dangers-to-watch-out-for-in-2019/

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Once it was fashionable to fret about the prospect of super-intelligent machines taking over the world. The past year showed that AI may cause all sorts of hazards long before that happens.

The latest AI methods excel at perceptual tasks such as classifying images and transcribing speech, but the hype and excitement over these skills have disguised how far we really are from building machines as clever as we are. Six controversies from 2018 stand out as warnings that even the smartest AI algorithms can misbehave, or that carelessly applying them can have dire consequences.

1. Self-crashing cars

After a fatal accident involving one of Uber’s self-driving cars in March, investigators found that the company’s technology had failed catastrophically, in a way that could easily have been prevented.

Carmakers like Ford and General Motors, newcomers like Uber, and a horde of startups are hurrying to commercialize a technology that, despite its immaturity, has already seen billions of dollars in investment. Waymo, a subsidiary of Alphabet, has made the most progress; it rolled out the first fully autonomous taxi service in Arizona last year. But even Waymo’s technology is limited, and autonomous cars cannot drive everywhere in all conditions.

What to watch for in 2019: Regulators in the US and elsewhere have so far taken a hands-off approach for fear of stifling innovation. The US National Highway Traffic Safety Administration has even signaled that existing safety rules may be relaxed. But pedestrians and human drivers haven’t signed up to be guinea pigs. Another serious accident in 2019 might shift the regulators’ attitudes.

2. Political manipulation bots

In March, news broke that Cambridge Analytica, a political consulting company, had exploited Facebook’s data sharing practices to influence the 2016 US presidential election. The resulting uproar showed how the algorithms that decide what news and information to surface on social media can be gamed to amplify misinformation, undermine healthy debate, and isolate citizens with different views from one another.

During a congressional hearing, Facebook CEO Mark Zuckerberg promised that AI itself could be trained to spot and block malicious content, even though it is still far from being able to understand the meaning of text, images, or video.

What to watch for in 2019: Zuckerberg’s promise will be tested in elections held in two of Africa’s biggest countries: South Africa and Nigeria. The long run-up to the 2020 US election has also begun, and it could inspire new kinds of misinformation technology powered by AI, including malicious chatbots. 

3. Algorithms for peace

Last year, an AI peace movement took shape when Google employees learned that their employer was supplying technology to the US Air Force for classifying drone imagery. The workers feared this could be a fateful step towards supplying technology for automating deadly drone strikes. In response, the company abandoned Project Maven, as it was called, and created an AI code of ethics.

Academics and industry heavyweights have backed a campaign to ban the use of autonomous weapons. Military use of AI is only gaining momentum, however, and other companies, like Microsoft and Amazon, have shown no reservations about helping out.

What to watch out for in 2019: Although Pentagon spending on AI projects is increasing, activists hope a preemptive treaty banning autonomous weapons will emerge from a series of UN meetings slated for this year.

4. A surveillance face-off

AI’s superhuman ability to identify faces has led countries to deploy surveillance technology at a remarkable rate. Face recognition also lets you unlock your phone and automatically tags photos for you on social media.

Civil liberties groups warn of a dystopian future. The technology is a formidable way to invade people’s privacy, and biases in training data make it likely to automate discrimination.

In many countriesChina especially—face recognition is being widely used for policing and government surveillance. Amazon is selling the technology to US immigration and law enforcement agencies.

What to watch out for in 2019: Face recognition will spread to vehicles and webcams, and it will be used to track your emotions as well as your identity. But we may also see some preliminary regulation of it this year, too.

5. Fake it till you break it

A proliferation of “deepfake” videos last year showed how easy it is becoming make fake clips using AI. This means fake celebrity porn, lots of weird movie mashups, and, potentially, virulent political smear campaigns.

Generative adversarial networks (GANs), which involve two dueling neural networks, can conjure extraordinarily realistic but completely made-up images and video. Nvidia recently showed how GANs can generate photorealistic faces of whatever race, gender, and age you want.

What to watch for in 2019: As deepfakes improve, people will probably start being duped by them this year. DARPA will test new methods for detecting deepfakes. But since this also relies on AI, it’ll be a game of cat and mouse.

6. Algorithmic discrimination

Bias was discovered in numerous commercial tools last year. Vision algorithms trained on unbalanced data sets failed to recognize women or people of color; hiring programs fed historic data were proven to perpetuate discrimination that already exists

Tied to the issue of bias—and harder to fix—is the lack of diversity across the AI field itself. Women occupy, at most, 30% of industry jobs and fewer than 25% of teaching roles at top universities. There are comparatively few black and Latin researchers as well.

What to expect in 2019: We’ll see methods for detecting and mitigating bias and algorithms that can produced unbiased results from biased data. The International Conference on Machine Learning, a major AI conference, will be held in Ethiopia in 2020 because African scientists researching problems of bias could have trouble getting visas to travel to other regions. Other events could also move.

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These ten enterprise M&A deals totaled over $40B in 2019

It would be hard to top the 2018 enterprise M&A total of a whopping $87 billion, and predictably this year didn’t come close. In fact, the top 10 enterprise M&A deals in 2019 were less than half last year’s, totaling $40.6 billion. This year’s biggest purchase was Salesforce buying Tableau for $15.7 billion, which would…

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These ten enterprise M&A deals totaled over $40B in 2019

It would be hard to top the 2018 enterprise M&A total of a whopping $87 billion, and predictably this year didn’t come close. In fact, the top 10 enterprise M&A deals in 2019 were less than half last year’s, totaling $40.6 billion.

This year’s biggest purchase was Salesforce buying Tableau for $15.7 billion, which would have been good for third place last year behind IBM’s mega deal plucking Red Hat for $34 billion and Broadcom grabbing CA Technologies for $18.8 billion.

Contributing to this year’s quieter activity was the fact that several typically acquisitive companies — Adobe, Oracle and IBM — stayed mostly on the sidelines after big investments last year. It’s not unusual for companies to take a go-slow approach after a big expenditure year. Adobe and Oracle bought just two companies each with neither revealing the prices. IBM didn’t buy any.

Microsoft didn’t show up on this year’s list either, but still managed to pick up eight new companies. It was just that none was large enough to make the list (or even for them to publicly reveal the prices). When a publicly traded company doesn’t reveal the price, it usually means that it didn’t reach the threshold of being material to the company’s results.

As always, just because you buy it doesn’t mean it’s always going to integrate smoothly or well, and we won’t know about the success or failure of these transactions for some years to come. For now, we can only look at the deals themselves.

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Jumia, DHL, and Alibaba will face off in African ecommerce 2.0

The business of selling consumer goods and services online is a relatively young endeavor across Africa, but ecommerce is set to boom. Over the last eight years, the sector has seen its first phase of big VC fundings, startup duels and attrition. To date, scaling e-commerce in Africa has straddled the line of challenge and…

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Jumia, DHL, and Alibaba will face off in African ecommerce 2.0

The business of selling consumer goods and services online is a relatively young endeavor across Africa, but ecommerce is set to boom.

Over the last eight years, the sector has seen its first phase of big VC fundings, startup duels and attrition.

To date, scaling e-commerce in Africa has straddled the line of challenge and opportunity, perhaps more than any other market in the world. Across major African economies, many of the requisites for online retail — internet access, digital payment adoption, and 3PL delivery options — have been severely lacking.

Still, startups jumped into this market for the chance to digitize a share of Africa’s fast growing consumer spending, expected to top $2 billion by 2025.

African e-commerce 2.0 will include some old and new players, play out across more countries, place more priority on internet services, and see the entry of China.

But before highlighting several things to look out for in the future of digital-retail on the continent, a look back is beneficial.

Jumia vs. Konga

The early years for development of African online shopping largely played out in Nigeria (and to some extent South Africa). Anyone who visited Nigeria from 2012 to 2016 likely saw evidence of one of the continent’s early e-commerce showdowns. Nigeria had its own Coke vs. Pepsi-like duel — a race between ventures Konga and Jumia to out-advertise and out-discount each other in a quest to scale online shopping in Africa’s largest economy and most populous nation.

Traveling in Lagos traffic, large billboards for each startup faced off across the skyline, as their delivery motorcycles buzzed between stopped cars.

Covering each company early on, it appeared a battle of VC attrition. The challenge: who could continue to raise enough capital to absorb the losses of simultaneously capturing and creating an e-commerce market in notoriously difficult conditions.

In addition to the aforementioned challenges, Nigeria also had (and continues to have) shoddy electricity.

Both Konga — founded by Nigerian Sim Shagaya — and Jumia — originally founded by two Nigerians and two Frenchman — were forced to burn capital building fulfillment operations most e-commerce startups source to third parties.

That included their own delivery and payment services (KongaPay and JumiaPay). In addition to sales of goods from mobile-phones to diapers, both startups also began experimenting with verticals for internet based services, such as food-delivery and classifieds.

While Jumia and Konga were competing in Nigeria, there was another VC driven race for e-commerce playing out in South Africa — the continent’s second largest and most advanced economy.

E-tailers Takealot and Kalahari had been jockeying for market share since 2011 after raising capital in the hundreds of millions of dollars from investors Naspers and U.S. fund Tiger Global Management.

So how did things turn out in West and Southern Africa? In 2014, the lead investor of a flailing Kalahari — Naspers — facilitated a merger with Takealot (that was more of an acquisition). They nixed the Kalahari brand in 2016 and bought out Takelot’s largest investor, Tiger Global, in 2018. Takealot is now South Africa’s leading e-commerce site by market share, but only operates in one country.

In Nigeria, by 2016 Jumia had outpaced its rival Konga in Alexa ratings (6 vs 14), while out-raising Konga (with backing of Goldman Sachs) to become Africa’s first VC backed, startup unicorn. By early 2018, Konga was purchased in a distressed acquisition and faded away as a competitor to Jumia.

Jumia went on to expand online goods and services verticals into 14 Africa countries (though it recently exited a few) and in April 2019 raised over $200 million in an NYSE IPO — the first on a major exchange for a VC-backed startup operating in Africa.

Jumia’s had bumpy road since going public — losing significant share-value after a short-sell attack earlier in 2019 — but the continent’s leading e-commerce company still has heap of capital and generates $100 million in revenues (even with losses).

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Airbnb’s New Year’s Eve guest volume shows its falling growth rate

Hello and welcome back to our regular morning look at private companies, public markets and the gray space in between. It’s finally 2020, the year that should bring us a direct listing from home-sharing giant Airbnb, a technology company valued at tens of billions of dollars. The company’s flotation will be a key event in…

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Airbnb’s New Year’s Eve guest volume shows its falling growth rate

Hello and welcome back to our regular morning look at private companies, public markets and the gray space in between.

It’s finally 2020, the year that should bring us a direct listing from home-sharing giant Airbnb, a technology company valued at tens of billions of dollars. The company’s flotation will be a key event in this coming year’s technology exit market. Expect the NYSE and Nasdaq to compete for the listing, bankers to queue to take part, and endless media coverage.

Given that that’s ahead, we’re going to take periodic looks at Airbnb as we tick closer to its eventual public market debut. And that means that this morning we’re looking back through time to see how fast the company has grown by using a quirky data point.

Airbnb releases a regular tally of its expected “guest stays” for New Year’s Eve each year, including 2019. We can therefore look back in time, tracking how quickly (or not) Airbnb’s New Year Eve guest tally has risen. This exercise will provide a loose, but fun proxy for the company’s growth as a whole.

The numbers

Before we look into the figures themselves, keep in mind that we are looking at a guest figure which is at best a proxy for revenue. We don’t know the revenue mix of the guest stays, for example, meaning that Airbnb could have seen a 10% drop in per-guest revenue this New Year’s Eve — even with more guest stays — and we’d have no idea.

So, the cliche about grains of salt and taking, please.

But as more guests tends to mean more rentals which points towards more revenue, the New Year’s Eve figures are useful as we work to understand how quickly Airbnb is growing now compared to how fast it grew in the past. The faster the company is expanding today, the more it’s worth. And given recent news that the company has ditched profitability in favor of boosting its sales and marketing spend (leading to sharp, regular deficits in its quarterly results), how fast Airbnb can grow through higher spend is a key question for the highly-backed, San Francisco-based private company.

Here’s the tally of guest stays in Airbnb’s during New Years Eve (data via CNBC, Jon Erlichman, Airbnb), and their resulting year-over-year growth rates:

  • 2009: 1,400
  • 2010: 6,000 (+329%)
  • 2011: 3,1000 (+417%)
  • 2012: 108,000 (248%)
  • 2013: 250,000 (+131%)
  • 2014: 540,000 (+116%)
  • 2015: 1,100,000 (+104%)
  • 2016: 2,000,000 (+82%)
  • 2017: 3,000,000 (+50%)
  • 2018: 3,700,000 (+23%)
  • 2019: 4,500,000 (+22%)

In chart form, that looks like this:

Let’s talk about a few things that stand out. First is that the company’s growth rate managed to stay over 100% for as long as it did. In case you’re a SaaS fan, what Airbnb pulled off in its early years (again, using this fun proxy for revenue growth) was far better than a triple-triple-double-double-double.

Next, the company’s growth rate in percentage terms has slowed dramatically, including in 2019. At the same time the firm managed to re-accelerate its gross guest growth in 2019. In numerical terms, Airbnb added 1,000,000 New Year’s Eve guest stays in 2017, 700,000 in 2018, and 800,000 in 2019. So 2019’s gross adds was not a record, but it was a better result than its year-ago tally.

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