Overnight success now requires a little more time

Ten years ago the iOS App Store launched — and the mobile revolution was off. Entrepreneurs everywhere rallied to take advantage, building category-defining consumer companies like Twitter, Uber, Lyft and Square, among many others.

There’s no better time for an entrepreneur to start a company than when a new platform like mobile emerges. The rising tide in these moments becomes a tsunami: Eager customers descend on services through word of mouth and new acquisition channels; there’s outsized press interest; and sales take off in part due to growth of the platform itself.

Now is not one of these periods. Mobile appears mature, and the next great enabling platform is still just past the horizon. That’s why many early-stage VCs have shifted their focus away from consumer and to other new enabling technologies, such as autonomous vehicles, blockchain and AI/ML.

I have a different view. I think now is a great time to build consumer companies, even without a new platform. There are three reasons for this. First, the internet has created big problems for humans, organizations and society, which entrepreneurs can attack at scale. Second, the first wave of mobile-enabled companies have laid a foundation — including processes, seasoned executives and business models — that new entrepreneurs can borrow. And third, mobile technology is still changing and evolving.

Let’s take a closer look at all three.

Solving big problems

The last wave of breakout companies created interactive platforms (Twitter, Snapchat, Instagram, etc.) that have entertained many. They didn’t solve big societal problems. There’s now a big need — and big opportunity — for companies that can help people save time, money and sanity, even as they build great businesses.

Most of us now realize the major problems that a connected, mobile, always-on world has wrought. These include:

  • Income inequality. Lower-income Americans are struggling more than ever. Entrepreneurs should be thinking of ways to help folks where they need it the most: the pocketbook. That might mean unlocking found money, ensuring that available financial resources are being used wisely or saving consumers from the growing number of “gotchas” imposed by financial institutions.
  • Too many choices. When you can buy or choose anything, it’s hard to pick what you actually want. There are wide-open opportunities for concierges, curation and trusted guides.
  • A lack of intimacy. With everything online and available at the touch of a keypad, genuine human interaction has become more rare. There’s a need for companies that can provide real care and curation for matters that affect our daily lives.

Newly available resources

After a decade of building companies for mobile, there are now untold stories, battle scars and people available for future companies to learn from. This makes it easier for startups to assemble playbooks and experienced teams. It also reduces the downside risk for investors, opening new paths to capital for companies that need it.

For instance, it’s now clear that consumer brands must define, own and curate an end-to-end experience. A great new example is GOAT, the online sneakerhead marketplace. Faced with a sneaker market full of rampant knock-offs, the founders invested in a capital- and time-intensive process to manually inspect every shoe for authenticity. The result is an experience that every sneakerhead loves and a breakthrough consumer brand.

Building a breakout consumer platform will be more complex, more challenging and often more capital-intensive than it was for the prior generation.

There are also lots of executives and teams that know how to lead and manage complex operations, especially on the ground. This is crucial to scale logistically complex ideas like Opendoor, Instacart and others.

The other thing needed to help scale these companies is capital. And right now, there are two particularly relevant new kinds of investors: 1) mega equity funds like SoftBank Vision Fund, and 2) alternative lending funds that provide non-dilutive capital to companies to finance the acquisition of traditional assets. Those capital sources enable companies like Opendoor (disclosure: I’m a personal investor) to own and manage a truly delightful end-to-end experience.

Mobile today is not mobile tomorrow

Mobile devices have come a long way over the last decade. And there will be many more meaningful improvements in the near future, allowing for new uses and new companies.

I anticipate breakthroughs that will boost the ability of the chips and subsystems on a phone to perform optimally for far longer. Right now, these are throttled due to heating issues and other problems. As companies solve these issues, they’ll create order of magnitude improvements on what our phones are capable of, bringing technologies like VR and AR, to take two examples, far forward into everyday use.

On the network side, 5G and subsequent buildouts will meaningfully change what kinds of bandwidth we can handle, enabling even more data and compute to be in the cloud.

Mobile today is about one-to-many broadcast platforms like Instagram, Twitter and Facebook. Tomorrow’s great consumer companies will leverage a better vector: one-to-one customer intimacy. Companies like Grove Collaborative (disclosure: Mayfield is an investor) are experiencing hypergrowth in part by using real people connecting with consumers over text to bring a curated, personalized experience to shopping for household staples. I expect this to be a major trend, with the companies that earn the right to communicate more with customers the ones that win.

Building a breakout consumer platform will be more complex, more challenging and often more capital-intensive than it was for certain titans of the prior generation. But for those with the vision and substance to bring a valuable service to the world that solves real problems, the resources and emerging technologies will be there to help create the next groundbreaking consumer brand.

Why the future of Chinese e-commerce is in its rural areas

China announced a mere 6.7 percent economic growth in July 2018, the lowest growth rate since 2016. Despite a slowdown in overall economic growth, Chinese e-commerce has only increased, accounting for 40 percent of all worldwide e-commerce today, compared to a mere 20 percent of the global retail market just three years ago.

The fast-paced growth of the e-commerce sector in China can be seen through rapidly expanding companies such as Pinduoduo, which went through a $1.5 billion U.S. IPO in mid-July. However, why has e-commerce continued to grow despite an overall economic slowdown in conjunction with urban market saturation? The answer to this question lies in China’s rural areas, with its untouched older demographic, potential for infrastructure development and government-backed initiatives.

An untouched older demographic primed for growth

The older demographic of China’s population, typically living in the Western rural areas of China, presents immense growth potential for e-commerce retailers, with the 60+ demographic numbering 241 million, representing nearly 20 percent of China’s total population.

With comparatively newer exposure to technology compared to younger urbanites, this older generation presents an untouched income stream for e-commerce. Chinese retailers have only recently begun to recognize this fact to shape their marketing initiatives accordingly, with companies such as Alibaba introducing this year a Taobao shopping app specifically designed to cater to those 50 and older.

In fact, a huge catalyst for Pinduoduo’s success is its popularity with users in this demographic, playing on social factors to promote use by older customers. However, additional user education and more elder-specific initiatives must be introduced to fully tap into this older demographic.

Infrastructure development for e-commerce

Lack of technological development in rural Chinese areas is another reason why e-commerce has not yet reached its full potential. Rural Western-based users make up a meager 27 percent of all internet users in China, with the vast majority of infrastructure developments being focused on China’s Eastern seaboard.

China’s e-commerce companies have begun to recognize the rural sector as having the largest potential for prosperity.

Lack of cellular infrastructure development runs in parallel with a similarly dismal rural logistics network, making it difficult to order and deliver e-commerce goods in the region. To counter this problem, JD.com received approval earlier this year from China’s Civil Aviation Administration to test a drone delivery network in the northwest Shaanxi province, with an aim to build more than 10,000 drone airports in the future, with a specific 185 being dedicated to deliver goods in the mountainous Sichuan region.

These developments are indicative of e-commerce companies recognizing the deficiencies in connecting rural consumers to the ability to purchase goods online, with potential for growth being huge in the next coming years.

Governmental backing and countryside rejuvenation

The Chinese government is also encouraging growth in the countryside, with this growth providing the opportunity for e-commerce to flourish accordingly.

The National Strategic Plan for Rural Vitalization from 2018 to 2022 aims to boost rural incomes and living standards, closing a widening wealth gap and boosting a slowing economy. Other government initiatives subsidize rural manufacturingrural drone development and much more. With this government backing, some in China are moving back to the countryside, with these initiatives developing jobs that re-attract former rural-to-urban migrants.

These returning migrants help spread the influence of e-commerce in rural areas through their familiarity with such platforms from their time in Chinese cities, thus increasing demand in these regions. Government initiatives to increase wealth in rural areas, whether through job creation or through regulated programmed development, help to grow e-commerce in China’s countryside by providing rural households with increased disposable income.

Simply put, rural China has not yet experienced the growth of e-commerce that has become so familiar to many urban Chinese. China’s e-commerce companies have begun to recognize the rural sector as having the largest potential for prosperity, with an older and newly online population, desperately needed infrastructure and logistical development, as well as with government-backing.

China’s rural areas present huge growth potential for e-commerce in the near-future, and represent one of the last untapped market areas for Chinese companies.

In venture capital, it’s still the age of the unicorn

This month marks the 5-year anniversary of Aileen Lee’s landmark article, “Welcome To The Unicorn Club”.

At the time, the piece defined a new breed of startup — the $1 billion privately held company. When Lee did her first count, there were 39 “unicorns”; an improbable, but not impossible number.. Today, the once-scarce unicorn has become a global herd with 376 companies on the roster and counting.

But the proliferation of unicorns begs raises certain questions. Is this new breed of unicorn artificially created? Could these magical companies see their valuations slip and fall out of the herd? Does this indicate an irrational exuberance where investors are engaging in wish fulfilment and creating magic where none actually existed?

List of “unicorn” companies worth more than $1 billion as of the third quarter of 2018

There’s a new “unicorn” born every four days

The first change has been to the geographic composition and private company requirement of the list. The original qualification for the unicorn study was “U.S.-based software companies started since 2003 and valued at over $1 billion by public or private market investors.” The unicorn definition has changed and here is the popular and wiki page definition we all use today: “A unicorn is a privately held startup company with a current valuation of US$1 billion or more.”

Beyond the expansion of the definition of terms to include a slew of companies from all over the globe, there’s been a concurrent expansion in the number of startup technology companies to achieve unicorn status. There is a tenfold increase in annual unicorn production.

Indeed, while the unicorn is still rare but not as rare as before. Five years ago, roughly ten unicorns were being created a year, but we are approaching one hundred new unicorns a year in 2018.

As of November 8, we have seen eighty one newly minted unicorns this year, which means we have one new unicorn every four days.

There are unicorn-sized rounds every day

These unicorns are also finding their horns thanks to the newly popularized phenomena of mega rounds which raise $100 million or more. These deals are ten times more common now, than they were only five years ago.   

Back in 2013, there were only about four mega rounds a month, but now there are forty mega rounds a month based on Crunchbase data. In fact, starting from 2015, public market IPO has for the first time no longer been the major funding source for unicorn size companies.

Unicorns have been raising money from both traditional venture capital but also more from the non-traditional venture capital such as SoftBank, sovereign wealth funds, private equity funds, and mutual funds.

Investors are chasing the value creation opportunity.   Most people probably did not realize that Amazon, Microsoft, Cisco, and Oracle all debuted on public markets for less than a $1 billion market cap (in fact only Microsoft topped $500 million), but today they together are worth more than $2 trillion dollars  

It means tremendous value was created after those companies came to the public market.  Today, investors are realizing the future giant’s value creation has been moved to the “pre-IPO” unicorn stage and investors don’t want to miss out.

To put things in perspective, investors globally deployed $13 billion in almost 20,000 seed & angel deals, and SoftBank was able to deploy the same $13 billion amount in just 2 deals (Uber and WeWork).  The SoftBank type of non-traditional venture world literally redefined “pre-IPO” and created a new category for venture capital investment.

Unicorns are staying private longer

That means the current herd of unicorns are choosing to stay private longer. Thanks to the expansion of shareholders private companies can rack up under the JOBS Act of 2012; the massive amount of funding available in the private market; and the desire of founders to work with investors who understand their reluctance to be beholden to public markets.

Elon Musk was thinking about taking Tesla private because he was concerned about optimizing for quarterly earning reports and having to deal with the overhead, distractions, and shorts in the public market.  Even though it did not happen in the end, it reflects the mentality of many entrepreneurs of the unicorn club. That said, most unicorn CEOs know the public market is still the destiny, as the pressure from investors to go IPO will kick in sooner or later, and investors expect more governance and financial transparency in the longer run.

Unicorns are breeding outside of the U.S. too

Finally, the current herd of unicorns now have a strong global presence, with Chinese companies leading the charge along with US unicorns. A recent Crunchbase graph indicated about 40% of unicorns are from China,, 40% from US, and the rest from other parts of the world.

Back in 2013, the “unicorn” is primarily a concept for US companies only, and there were only 3 unicorn size startups in China (Xiaomi, DJI, Vancl) anyways.  Another change in the unicorn landscape is that, China contributed predominantly consumer-oriented unicorns, while the US unicorns have always maintained a good balance between enterprise-oriented and consumer-oriented companies.  One of the stunning indications that China has thriving consumer-oriented unicorns is that China leads US in mobile payment volume by hundredfold.

The fundamentals of entrepreneurship remain the same

Despite the dramatic change of the capital market, a lot of the insights in Lee’s 5-year old blog are still very relevant to early stage entrepreneurs today.

For example, in her study, most unicorns had co-founders rather than a single founder, and many of the co-founders had a history of working together in the past.

This type of pattern continues to hold true for unicorns in the U.S. and in China. For instance, the co-founders of Meituan (a $50 billion market cap company on its IPO day in September 2018) went to school together and had co-founded a company before

There have been other changes. In the past three months alone, four new US enterprise-oriented unicorns have emerged by selling directly to developers instead of to the traditional IT or business buyers; three China enterprise-oriented SaaS companies were able to raise mega rounds.  These numbers were unheard of five years ago and show some interesting hints for entrepreneurs curious about how to breed their own unicorn.

The new normal is reshaping venture capital 

Once in a while, we see eye-catching headlines like “bubble is larger than it was in 2000.”   The reality is companies funded by venture capital increased by more than 100,000 in the past five years too. So the unicorn is still as rare as one in one thousand in the venture backed community.

What’s changing behind the increasing number of unicorns is the new normal for both investors and entrepreneurs. Mega rounds are the new normal; staying private longer is the new normal; and the global composition of the unicorn club is the new normal. 

Just look at the evidence in the venture industry itself. Sequoia Capital, the bellwether of venture capital, raised a whopping $8 billion global growth mega fund earlier this year under pressure from SoftBank and its $100 billion mega-fund. And Greylock Partners, known for its focus and success in leading early stage investment, recently led a unicorn round for the first time in its 53-year history.  

It’s proof that just as venture capitalists have created a new breed of startups, the new startups and their demands are reshaping venture capital to continue to support the the companies they’ve created.

Placing bets beyond the venture hubs of New York and Silicon Valley

If geographies were companies, Silicon Valley and New York would be the incumbents — successful today and possibly impregnable — and, like all incumbents, their outsized advantages obscure significant vulnerabilities. Not least of these are high prices and entrenched thinking that can make adapting to new situations difficult.

A dozen venture capitalists spent three days in the South — Charlotte, Columbia, and Atlanta — to learn what it might take to begin investing in the region as an alternative. It was the sequel to a trip some of us took earlier this year to the heartland. And yet again, we saw places and met people with assets Silicon Valley can only dream about.

The cities we visited represent a new breed of challenger to the geographic dominance of venture capital’s leading centers, who — if they can cover the table stakes — bring advantages the Valley may struggle to capture.

First; diversity. It helps startups to bring people together with a range of life experiences, so places like Columbia, Charlotte, and Atlanta should be natural winners. Racial diversity, yes — anchored in part by the strong presence of historically black colleges and universities, of which we visited several — and also diversity of their economies.

In Atlanta (the second-largest majority-black metro in the country) in particular, there’s a wide range of corporate partners (read: customers for startups). Atlanta has the third-most Fortune 500 companies of any city, and you need to go down to #11 before you get any two in the same industry. (Think UPS, Coca-Cola, Delta, Home Depot, and so forth.)

Second; these places have a history of overcoming adversity. Many students we met were first-generation college kids, whose parents and grandparents learned to climb over the brick wall of racism and passed on that grit. The startups that thrive despite the rocky soil become less fragile, less precariously perched on the peak of this month’s hype cycle.

If a startup can make it in Orangeburg, SC, a manufacturing town with a median household income of $29k, it can make it anywhere. Many founders in Silicon Valley have had it so good they can no longer smell money. Startups, unlike many other kinds of projects (like learning to play music), simply require the right timing and dosage of adversity.

What will it take for these places to realize their potential?

Their engines are warm and running. We were floored by the consistently exceptional quality of the startups marshalled by Kathryn Finney at Atlanta’s digital undivided, and felt right at home with the founders who Collective Hustle’s Sam Smith gathered around a table in Charlotte.

A few drops of mentorship and capital will crystallize even more progress. We met students who devoured every word of the tech blogs we all read, and still craved someone with first-hand knowledge, to warn them away from dead ends or confirm their intuitions. Several of us said we’d be happy to videoconference in to classes, or come back again and visit.

We invited our hosts in the South to spend a few days with us in the bubble. We realize that providing mentorship at scale is another matter, and we’re thinking about how to do that. We did notice that big technology companies — Google, Microsoft, Bloomberg — have already done a good job of showing up for recruiting or startup-support programs.

While there are angel investors in every market, it’s clear that most rich people (understandably) need a basic understanding of that strange bird of startup investing. We heard story after story of angels who focus on safe bets (good luck!), ask for control over startups in modest five-figure investments, and fail to take advantage of the worthwhile standards from more developed ecosystems. Even the local angel groups, where they exist, tended to reinforce bad behavior as often as they shared good ones (as organized angel groups often do).

Government participates more actively in these ecosystems — starting with the hosts of our trip, Representatives Tim Ryan (OH), Ro Khanna (CA), and Jim Clyburn (SC). Creating an environment for startups is a completely different beast than traditional “smokestack chasing” economic development (where a city tries to lure big employers to bring a massive facility).

It’s more about identifying individual champions (one mayor struggled to tell us who the active investors were in their community), creating the living conditions that technology employees want (art, food, and fast, reliable internet among others), and protecting the green shoots that bust their way through the concrete. Governments can use the bully pulpit to draw attention to nascent victories at zero cost to taxpayers.

Investors from Silicon Valley or New York need to stop asking founders to relocate. So many founders had heard the tired “I’ll consider investing… if you move” story. This is borderline bad behavior — asking a founder to uproot their life because it’s more convenient for the investor. While investors might believe they’re making a recommendation in the company’s best interest (“it’s easier to succeed in a more established place”), founders have unfair home court advantages (knowing talent, customers, etc.).

What will we investors need to learn, if we’re to participate in the growth of these markets?

We need to watch the assumptions our words reveal. People who live in coastal cities talk like a duck. We’ll benefit from reading the room when words like “SaaS” or “LP” need explanation. Getting “ramen profitable” may assume a founder has family with whom they can live — one founder told us that “it feels like you need $500k in funding to even try to do that.”

Often the first step is something other than a direct investment. Investors might participate in a few local events, or encourage a portfolio company to open a second office (as one did from our last trip to South Bend), or build relationships through mentoring and coaching. Direct investments can start small — we had founders asking for investment rounds in the tens of thousands of dollars, i.e., with one fewer zero than the smallest rounds in bubbleland.

We’ll need to embrace the communities that hold these places together: Churches are especially important outside the coasts. More than one founder told us about the role The Creator plays in their startup’s creation. Baptist, AME, and Methodist churches have long undergirded economic development in these cities. Startups harness those trusted networks to find teammates and customers. Investors who see the importance of churches will find deals. (Silicon Valley’s atheist streak makes this a new muscle for us out-of-towners.)

Every place has its own shape. Charlotte, despite being near Research Triangle, gets relatively little flow of talent from Raleigh-Durham. The economic boom there also, ironically, can make it harder for a startup to compete for talent and attention. In Orangeburg, we saw a strong startup that planned to move to Baltimore — and none of us could fault those founders for choosing to go to a more active startup place. Several others in Columbia banded together to occupy SOCO, in a new real estate development, planting seeds.

Atlanta almost has it all right now — talent, experienced angels, role model founders who actively mentor rookies, and quality of life (the BeltLine felt like what the High Line wishes it were). Atlanta has that most-important and elusive startup quality: momentum. (Fund LPs may actually have some of the best opportunities there, because just a couple of slightly bigger local venture funds would smooth the transition between different stages in a company’s life. More investors might get to bet on a Mailchimp before it prides itself on not needing them.)

In our country, where everyone is supposed to have a real chance at extraordinary opportunity, one question hung over our trip: is geography… destiny? Can a kid at Benedict College in Columbia create one of the world’s defining startups? Fast forward the clock, and we believe we may see that. Our goal is to participate and support it. Some of the places we visited — with their combination of diversity and overcoming adversity — are irresistible bets on the future of startups in America, maybe even on the future of America.

Additional credit to Karin Klein, Bloomberg Beta; Shiyan Koh, Hustle Fund; and Scott Shane, Comeback Capital. 

The top 10 cities for $100M VC rounds in 2018 so far

Crunchbase News recently profiled a selection of U.S. companies’ largest VC raised in 2018, and no surprise here: the 10 largest rounds all topped out well north of $100 million.

A major driver of global venture dollar growth is the relatively recent phenomenon of companies raising $100 million or more in a single venture round. We’ve called these nine and 10-figure deals, which shine brightly in the media and are hefty enough to bend the curve of VC fund sizes upwards, “supergiants” after their stellar counterparts.

And like stars, venture-backed companies tend to originate and co-exist in clusters, while the physical space between these groups is largely empty.

We noticed that many of the companies behind these supergiant rounds are headquartered in just a few metro areas around the United States. In this case, it’s mostly just the SF Bay Area, plus others scattered between Boston, Los Angeles, San Diego and one (Magic Leap) in the unfortunately named Plantation, Florida.

The San Francisco Bay Area is perhaps one of the best-known tech and startup hubs in the world. Places like Boston, NYC and Los Angeles, among others, are perhaps just as well-known. But how do these cities stack up as clusters for companies raising supergiant rounds?


That question got us wondering how these locales rank against other major metropolitan areas throughout the world. In the chart below, we’ve plotted the count of supergiant venture rounds1 topping out at $100 million or more through November 5. These numbers are based off of reported data in Crunchbase, exclude private equity rounds and do not account for deals that may have already been closed but haven’t been publicly announced yet.

Although U.S.-based companies have raised more supergiant rounds (168 year to date) than their Chinese counterparts (160 year to date), Chinese companies raise much bigger rounds, even at this supergiant size class.

How much more? U.S. companies have raised $38.4 billion, year to date, in nine and 10-figure venture rounds alone. Chinese companies have raised $69 billion across their 160 supergiant deals, which includes the largest-ever VC deal: a $14 billion Series C round raised by Ant Financial.

2018 in perspective

2018 is already a record year for venture funding worldwide. With more than $275 billion in projected total venture dollar volume so far, 2018’s year-to-date numbers have already eclipsed 2017’s full-year figures (a projected $220 billion, roughly) by more than $55 billion.2

And there’s still about eight weeks left to go before it’s New Year’s Eve.

  1. We use the same classification rules for what is and is not a “venture” round as we’ve used in our quarterly reports. Check out the methodology section of our most recent global VC report, from Q3 2018, to learn more about how Crunchbase News categorizes rounds.
  2. We’re referring to the same type of projected data we use in the quarterly reports. Check out the methodology section of our most recent global VC report, from Q3 2018, to learn more about how Crunchbase News uses projected and reported data.

Three challenges facing blockchain technology

Nearly five years ago, Overstock.com became the first major retailer to accept bitcoin as a form of payment. It now accepts many top cryptocurrencies. As a member of the senior executive team and board of directors at Overstock.com, I had a front-row seat to those decisions.

It didn’t take long for the Overstock team to realize that bitcoin’s underlying blockchain technology held great promise beyond cryptocurrencies. We also knew that for blockchain technology to reach its full potential, the startup companies advancing its use would need both financial and human capital support.

Overstock set up a venture capital blockchain incubator, Medici Ventures, to do just that.

We believe blockchain technology will eventually impact many industries. We are already involved in promising developments in areas like capital markets, money transmission and banking, voting, supply chain, property and self-sovereign identity. But there is still a long way to go before blockchain technology can realize its true potential.

Here are the three most important challenges facing more widespread adoption of blockchain technology right now.

Finding good enterprise-level blockchain software developers

The world has become so reliant on computers, to the point where virtually every company now has need for software development. In this environment, where demand grows exponentially, good software development talent is hard to find. Game-changing talent is rarer still.

Because blockchain is a new field of technology, there are fewer talented enterprise-level software developers who understand it well. Those who do can practically write their own tickets. While this is an enviable position for them, it limits many companies from developing engaging and transformative blockchain-based applications.

Let’s remember that we are in the early days of blockchain.

At Medici Ventures, we provide regular internal training to help our software developers climb this important learning curve. In this training — which we do in educational presentations which sometimes include accelerated coursework — our teams often present discoveries made when developing on one project, with the hope that the solutions may benefit those working on other projects. This approach lets us cross-pollinate our industries and our disciplines, so creative development and innovation become rising tides rather than isolated spikes.

The time spent learning is well worth it; it is why many of our portfolio companies rely not just on our venture capital, but also our human capital. Until there is a regular pipeline of well-qualified blockchain developers, the shortage of great talent will continue to be a struggle for the advancement of the technology.

Avoiding the temptation of regulation

Like many of their voting constituents, Congress and state legislatures are just becoming aware of blockchain. In some ways, this is good news: Political engagement will increase awareness and interest for utilizing blockchain technology and help drive adoption of these new ideas. Unfortunately, it also brings the temptation of regulation to an emerging market.

I get concerned when regulators and legislators get a whiff of any kind of technological development because they are tempted to regulate it. When U.S. Securities and Exchange Commission (SEC) chair Jay Clayton stated that he considered all initial coin offerings (ICOs) to be securities rather than commodities, and therefore subject to his organization’s regulation, Clayton brought an ICO boom to a screeching halt. While Chairman Clayton and others at the SEC have subsequently modified that stance, this regulatory tendency to fear what is new is dangerous.

The interconnectedness of the world means its adoption will probably take root and bloom quickly.

Technology — and the advancement of blockchain — should not be regulated. In the 1990s, when the internet’s potential was becoming evident, legislators opted not to regulate it. That bipartisan decision led to the open-market creation of the much-lauded “information superhighway” and the power of the internet today.

Certainly, there will be use cases that may require regulation as blockchain applications develop and proliferate. But the growth of blockchain technology will be best nurtured when it is free and unfettered from regulation.

Reaching critical mass

Cryptocurrencies and digital wallets built on blockchain are great uses of the technology. In order for cryptocurrencies to proliferate in use and stabilize in price, and for digital wallets to get widespread adoption, consumers need to spend cryptocurrencies more and merchants need to accept them. A great example of this working the right way is Colu, an exciting new company I recently saw in action when I was in Tel Aviv, Israel. Colu is a digital wallet that uses blockchain technology to create local currencies. People simply download the app, add money and shop locally. The app highlights local establishments and makes shopping convenient. And it is dazzling people in Tel Aviv!

The same can be said of other blockchain-based applications like secure remote digital voting. West Virginia recently became the first state to allow overseas citizens to vote remotely using a blockchain-driven app. The West Virginia program was tested in the May primary and was used in this November’s general election.

We’ll know blockchain technology has become mainstream when we are no longer talking about it.

Some critics have been quick to disparage real efforts to create digital voting with strictly theoretical worries. In reality, the rollout in West Virginia is a very focused solution to a specific issue: low overseas voter participation. The current system is broken. A blockchain-driven digital voting app is a clear solution. Anyone but critics of progress should eagerly support West Virginia’s efforts until there is an actual reason to worry.

Once any blockchain application is embraced in sufficient numbers by both the using and accepting sides, the impressive software will become an invaluable and ubiquitous tool. More widespread adoption of blockchain’s most beneficial use cases will trigger network effects that will multiply the benefits.

Let’s remember that we are in the early days of blockchain. Many industry observers seem to be in a rush to declare blockchain a mainstream technology. As enthusiastic as I am in my support of blockchain, I would not yet call it mainstream. The interconnectedness of the world means its adoption will probably take root and bloom quickly. We’ll know blockchain technology has become mainstream when we are no longer talking about it, but we are simply using it in everyday ways.

I am thrilled to see digital purchases made and remote votes cast in elections with this game-changing technology. As developers, investors and companies continue to focus on using and advancing blockchain, we will see that finding good enterprise-level blockchain software developers, letting blockchain grow free from unnecessary regulation and achieving critical mass use are the next important steps in the growth and adoption of this world-changing technology.

Three ways to avoid bias in machine learning

At this moment in history it’s impossible not to see the problems that arise from human bias. Now magnify that by compute and you start to get a sense for just how dangerous human bias via machine learning can be. The damage can be twofold:

  • Influence. If the AI said so it must be true… people trust outputs of AI, so if human bias is missed in the training it could compound the problem by infecting more people;
  • Automation. Sometimes AI models are plugged into a programmatic function, which could lead to the automation of bias. 

But there is potentially a silver machine-learned lining. Because AI can help expose truth inside messy data sets, it’s possible for algorithms to help us better understand bias we haven’t already isolated, and spot ethically questionable ripples in human data so we can check ourselves. Exposing human data to algorithms exposes bias, and if we are considering the outputs rationally, we can use machine learning’s aptitude for spotting anomalies.

But the machines can’t do it on their own. Even unsupervised learning is semi-supervised, as it requires data scientists to choose the training data that goes into the models. If a human is the chooser, bias can be present. How the heck do we tackle such a bias beast? We will attempt to pick it apart.

The landscape of ethical concerns with AI

Bad examples abound. Consider the finding from Carnegie Mellon that showed that women were shown significantly fewer online ads for high-paying jobs than men were. Or recall the sad case of Tay, Microsoft’s teen slang Twitter bot that had to be taken down after producing racist posts.

In the near future, such mistakes could result in hefty fines or compliance investigation, a conversation that’s already occurring in the U.K. parliament. All mathematicians and machine learning engineers should consider bias to some degree, but that degree varies from instance to instance. A small company with limited resources will often be forgiven for accidental bias as long as the algorithmic vulnerability is fixed quickly; a Fortune 500 company, which presumably has the resources to ensure an unbiased algorithm, will be held to a tighter standard.

Of course, an algorithm that recommends novelty T-shirts does not need nearly as much oversight as an algorithm that decides what dose of radiation to give to a cancer patient. It’s these high-stakes decisions that will become the most pronounced when legal liability enters the discussion.

It’s important for builders and business leaders to establish a process for monitoring the ethical behavior of their AI systems.

Three keys to managing bias when building AI

There are signs of existing self-correction in the AI industry: Researchers are looking at ways to reduce bias and strengthen ethics in rule-based artificial systems by taking human biases into account, for example.

These are good practices to follow; it’s important to be thinking proactively about ethics regardless of the regulatory environment. Let’s take a look at several points to keep in mind as you work on your AI.

1. Choose the right learning model for the problem.

There’s a reason all AI models are unique: Each problem requires a different solution and provides varying data resources. There’s no single model to follow that will avoid bias, but there are parameters that can inform your team as it’s building.

For example, supervised and unsupervised learning models have their respective pros and cons. Unsupervised models that cluster or do dimensional reduction can learn bias from their data set. If belonging to group A highly correlates to behavior B, the model can mix up the two. And while supervised models allow for more control over bias in data selection, that control can introduce human bias into the process.

It’s better to find and fix vulnerabilities now than to have regulators find them later on.

Non-bias through ignorance — excluding sensitive information from the model — may seem like a workable solution, but it still has vulnerabilities. In college admissions, sorting applicants by ACT scores is standard, but taking their ZIP code into account might seem discriminatory. But because test scores might be affected by the preparatory resources in a given area, including the ZIP code in the model could actually decrease bias.

You have to require your data scientists to identify the best model for a given situation. Sit down and talk them through the different strategies they can take when building a model. Troubleshoot ideas before committing to them. It’s better to find and fix vulnerabilities now — even if it means taking longer — than to have regulators find them later on.

2. Choose a representative training data set.

Your data scientists may do much of the leg work, but it’s up to everyone participating in an AI project to actively guard against bias in data selection. There’s a fine line you have to walk. Making sure the training data is diverse and includes different groups is essential, but segmentation in the model can be problematic unless the real data is similarly segmented.

It’s inadvisable — both computationally and in terms of public relations — to have different models for different groups. When there is insufficient data for one group, you could possibly use weighting to increase its importance in training, but this should be done with extreme caution. It can lead to unexpected new biases.

For example, if you have only 40 people from Cincinnati in a data set and you try to force the model to consider their trends, you might need to use a large weight multiplier. Your model would then have a higher risk of picking up on random noise as trends — you could end up with results like “people named Brian have criminal histories.” This is why you need to be careful with weights, especially large ones.

3. Monitor performance using real data.

No company is knowingly creating biased AI, of course — all these discriminatory models probably worked as expected in controlled environments. Unfortunately, regulators (and the public) don’t typically take best intentions into account when assigning liability for ethical violations. That’s why you should be simulating real-world applications as much as possible when building algorithms.

It’s unwise, for example, to use test groups on algorithms already in production. Instead, run your statistical methods against real data whenever possible. Ask the data team to check simple test questions like “Do tall people default on AI-approved loans more than short people?” If they do, determine why.

When you’re examining data, you could be looking for two types of equality: equality of outcome and equality of opportunity. If you’re working on AI for approving loans, result equality would mean that people from all cities get loans at the same rates; opportunity equality would mean that people who would have returned the loan if given the chance are given the same rates regardless of city. Without the latter, the former could still hide if one city has a culture that makes defaulting on loans common.

Result equality is easier to prove, but it also means you’ll knowingly accept potentially skewed data. While it’s harder to prove opportunity equality, it is at least valid morally. It’s often practically impossible to ensure both types of equality, but oversight and real-world testing of your models should give you the best shot.

Eventually, these ethical AI principles will be enforced by legal penalties. If New York City’s early attempts at regulating algorithms are any indication, those laws will likely involve government access to the development process, as well as stringent monitoring of the real-world consequences of AI. The good news is that by using proper modeling principles, bias can be greatly reduced or eliminated, and those working on AI can help expose accepted biases, create a more ethical understanding of tricky problems and stay on the right side of the law — whatever it ends up being.

Africa Roundup: Local VC funds surge, Naspers ramps up and fintech diversifies

Africa’s VC landscape is becoming more African with an increasing number of investment funds headquartered on the continent and run by locals, according to Crunchbase data summarized in this TechCrunch feature.

Drawing on its database and primary source research, Crunchbase identified 51 “viable” Africa-focused VC funds globally—defining viable as formally established entities with 7-10 investments or more in African startups, from seed to series stage.

Of the 51 funds investing in African startups, 22 (or 43 percent) were headquartered in Africa and managed by Africans.

Of the 22 African managed and located funds, 9 (or 41 percent) were formed since 2016 and 9 are Nigerian.

Four of the 9 Nigeria located funds were formed within the last year: Microtraction, Neon Ventures, Beta.Ventures, and CcHub’s Growth Capital fund.

The Nigerian funds with the most investments were EchoVC (20) and Ventures Platform (27).

Notably active funds in the group of 51 included Singularity Investments (18 African startup investments) Ghana’s Golden Palm Investments (17) and Musha Ventures (36).

The Crunchbase study also tracked more Africans in top positions at outside funds and  the rise of homegrown corporate venture arms.

One of those entities with a corporate venture arm, Naspers, announced a massive $100 million fund named Naspers Foundry to support South African tech startups. This is part of a $300 million (1.4 billion Rand) commitment by the South African media and investment company to support South Africa’s tech sector overall. Naspers Foundry will launch in 2019.

The initiatives lend more weight to Naspers’ venture activities in Africa as the company has received greater attention for investments off the continent (namely Europe, India and China), as covered in this TechCrunch story.

“Naspers Foundry will help talented and ambitious South African technology entrepreneurs to develop and grow their businesses,” said a company release.

“Technology innovation is transforming the world,” said Naspers chief executive Bob van Dijk. “The Naspers Foundry aims to both encourage and back South African entrepreneurs to create businesses which ensure South Africa benefits from this technology innovation.”

After the $100 million earmarked for the Foundry, Naspers will invest ≈ $200 million over the next three years to “the development of its existing technology businesses, including OLX,  Takealot, and Mr D Food…” according to a release.

In context, the scale of this announcement is fairly massive for Africa. According to recently summarized Crunchbase data, the $100 million Naspers Foundry commitment dwarfs any known African corporate venture activity by roughly 95x.

The $300 million commitment to South Africa’s tech ecosystem signals a strong commitment by Naspers to its home market. Naspers wasn’t ready to comment on if or when it could extend this commitment outside of South Africa (TechCrunch did inquire).

If Naspers does increase its startup and ecosystem funding to wider Africa— given its size compared to others—that would be a primo development for the continent’s tech sector.

If mobile money was the first phase in the development of digital finance in Africa, the next phase is non-payment financial apps in agtech, insurance, mobile-lending, and investech, according to a report by Village Capital covered here at TechCrunch.

In “Beyond Payments: The Next Generation of Fintech Startups in Sub-Saharan Africa,” the venture capital firm and their reporting partner, PayPal, identify 12 companies it determined were “building solutions in fintech subsectors outside of payments.”

Village Capital’s work gives a snapshot of these four sub-sectors — agricultural finance, insurtech, alternative credit scoring and savings and wealth — including players, opportunities and challenges, recent raises and early-stage startups to watch.

The report highlights recent raises by savings startup PiggybankNG and Nigerian agtech firm FarmCrowdy. Village Capital sees the biggest opportunities for insurtech startups in five countries: South Africa, Morocco, Egypt, Kenya and Nigeria.

In alternative credit scoring and lending it sees blockchain as a driver of innovation in reducing “both transaction costs and intermediation costs, helping entrepreneurs bypass expensive verification systems and third parties.”

The Founders Factory expanded its corporate-backed accelerator to Africa, opening an office in Johannesburg with the support of some global and local partners.

This is Founders Factory’s first international expansion and the goal is “to scale 100 startups across Sub-Saharan Africa in five years,” according the accelerator’s communications head, Amy Grimshaw.

Founders Fund co-founder Roo Rogers will lead the new Africa office. Standard Bank is the first backer, investing “several million funds over five years,” according to Grimshaw.

The Johannesburg accelerator will grow existing businesses through a bespoke six-month program, while an incubator will build completely new businesses focused on addressing key issues on the continent.

Founder Funds will hire over 40 full-time specialists locally, covering all aspects needed to scale its startups including product development, UX/UI, engineering, investment, business development and, growth marketing. This TechCrunch feature has more from Founders Fund management on the outlook for the new South Africa accelerator.

More Africa Related Stories @TechCrunch

How a Ugandan prince and a crypto startup are planning an African revolution

Marieme Diop and Shikoh Gitau to speak at Startup Battlefield Africa

Flutterwave and Ventures Platform CEOs will join us at Startup Battlefield Africa

African Tech Around the Net

A lot is happening at Flutterwave right now—[E departs] 

Amazon Web Services to open data centres in Cape Town in 2020

Vodacom Business expands its fixed connectivity network in Africa

SA’s Sun Exchange raises $500k from Alphabit

IBM, AfriLabs partner to expand digital skills across 123 hubs in 34 countries

Victor Asemota to lead VC firm Alta Global Ventures’s business in Africa

Bank, local hub launch $1-million fund for Somali startups