The Fallacy of Predictions

There is a popular joke (attributed to Niels Bohr): “It is difficult to make predictions, especially about the future.”

I remembered it when I picked up the March-April 2020 issue of the MIT Technology Review.

Subtitled “The prediction issue,” it showcased 10 predicted breakthrough technologies of the 2020s. In addition, the Review invited a dozen or so leading futurologists to predict which technology trends will dominate in 2020-2030. As Gideon Litchfield, the editor-in-chief, wrote introducing the issue: “…the point of futurism isn’t to guess the future; it’s to challenge your assumptions about the present so the future doesn’t catch you off guards.”

Characteristically, none of the predicted breakthrough technologies – and none of the proposed future trends – even mentioned the threat of worldwide pandemic like the one that is currently ravaging the globe.

No, I am not criticizing the writers and the editorial staff of the MIT Technology Review for making “wrong” predictions. My question is, have they been as caught off guard by the COVID-19 pandemic as the rest of us mere mortals?

The fallacy of predictions struck me again when I opened the 2019 Global Health Security Index, the first comprehensive assessment of the health security capabilities across 195 nations. The Index specifically focused on nations’ preparedness for infectious disease outbreaks that can lead to international epidemics and pandemics.

To the credit of its authors, the Index finds no single country fully prepared for epidemics or pandemics: the average overall score among all 195 countries was 40(!) of a possible 100.

But what genuinely surprised me were the scores that the Index assigned to individual countries. The United States led the world in the overall preparedness score (83.5) with the United Kingdom coming a close second (77.9). The U.S. also scored the highest in a few specific categories, including Prevention of the Emergence of Pathogens; Early Detection & Reporting of Epidemics; and Sufficient & Robust Health System to Protect Health Workers. The U.S. was second after the U.K. in the category Rapid Response to the Spread of an Epidemic.

What is the predictive power of the Index given the fact that the U.S. and the U.K. are among the countries with the highest per capita numbers of COVID-19 infections and COVID-19-related deaths?

In contrast, countries that did a reasonably good job in preventing the spread of the virus and keeping the death toll at a reasonably low level did not score particularly high. For example, the Czech Republic was only 48th on the overall score, and Iceland even lower, 58th. The Czech Republic was 57th in the category of Rapid Response to the Spread of an Epidemic, with Iceland being lower again, only 66th.

What were the assumptions about the present that led to the low rating of both countries that responded with admirable agility when facing a real, not imagined, crisis?

Like every normal human being, I love guessing about what will happen tomorrow. And I know that organizations need to predict the future to plan the next steps and foresee upcoming threats and opportunities. Yet, before we rush into a new set of predictions – as some consultancies have already begun doing – let’s pause and first explain to ourselves what happened.

As the next step, let’s challenge our assumptions about the present. Real present not assumed. And then – only then! – carefully resume predicting. Perhaps.

Check out my eBook, “We the People of the Crowd…,” a collection of stories about crowdsourcing reflecting my personal experience in working with corporate and nonprofit clients.

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Innovation and Freedom

With waves of profound technological change rocking every corner of the global economy, innovation isn’t a luxury anymore, not even a matter of choice – it’s a means of survival.  The mantra “innovate or die” may have become a cliché, yet it correctly reflects the contemporary business environment in which companies must relentlessly innovate to just stay in business.

Unfortunately, managing the innovation process in a sustainable way turned out to be difficult for a lot of organizations. Many corporate innovation leaders have failed to establish the infrastructure and processes needed to run efficient innovation programs and instead are wasting time talking about the elusive “culture of innovation.”

Sure, it’s impossible to ignore the importance of the human component in any corporate process, including innovation. But it’s much more important to identify specific factors affecting the innovation process to be able to improve it in a systematic way.

One such factor that, quite surprisingly, doesn’t get much attention is freedom. Yes, freedom. It’s very simple: in order to innovate, one needs freedom – and this applies to innovation at the individual, organizational, and national levels.

Freedom from being discriminated  

A case in point is the effect on innovation of U.S. anti-discrimination laws. A 2016 study showed that U.S. state-level employment nondiscrimination acts (ENDAs)—laws that prohibit discrimination based on sexual orientation and gender identity—spur innovation. U.S. public companies headquartered in states that have passed ENDAs experienced an 8% increase in the number of patents (and an 11% increase in their quality) relative to companies headquartered in states that have no ENDAs.

Another study showed a positive effect on innovation of two social liberalization policies: the legalization of same-sex civil unions and medical marijuana. In contrast, the laws setting additional restrictions on abortion had a negative effect on innovation at the state level.

It’s therefore hardly a coincidence that the two arguably most innovative U.S. states, California and Massachusetts, have traditionally been drivers of social liberalization: California was the first state to legalize medical marijuana in 1996, and Massachusetts the first state to legalize same-sex marriages in 2004.

No, I’m not saying that sexual minorities or people smoking weed are intrinsically more innovative. My point is that innovation implies a certain level of individual freedoms, including freedom from being discriminated for whatever reason.

The labor laws of innovation

Interestingly, labor laws have also been shown to have a positive effect on innovation. For example, the staggered passage of wrongful discharge laws (WDL) (the laws providing employees with greater protection than employment-at-will) across the U.S. states created a “natural experiment” assessing their impact on the innovation output. And this impact turned out to be quite impressive: the adoption of WDL resulted in a rise in the annual number and quality of patents issued to a state, an effect starting to emerge two years after the WDL passage in this state.

The above data indicate that innovation is fostered by limiting firms’ ability to discharge their employees at will.  The authors of the study call this phenomenon an “insurance effect”: feeling increased protection from negative consequences of failure, employees are more committed to the engagement in risky innovative projects. In other words, providing employees with immunity for failed innovation projects might be a better way to promote innovation than by “celebrating failures.”

Innovation and political freedoms

There is one more level at which innovation can be affected and which is almost never considered in the literature: the level of political and individual freedoms in individual countries. I first came across this point back in 2014 while reviewing the 2013 Global Innovation Index, a collaborative project of Cornell University, INSEAD, and the World Intellectual Property Organization. The Index ranked the innovation capabilities of 142 countries by using 84 indicators, which included, among others, the quality of higher education, availability of venture capital and government support.

Even a brief look at the Index led me to a curious observation: the top of the ranking was heavily populated by countries representing established democracies (according to the 2013 Freedom of the World Report). The reverse was also true: the bottom of the Index was stacked with countries with an extremely low level of democratic development.

To give this observation statistical support, I used the data from the 12th (2019) edition of the Global Innovation Index that analyzes global innovation performance of approximately 130 economies (Y-axis) and plotted it against the political freedom rankings taken from the Democracy Index 2019 composed by the Economist Intelligence Unit (X-axis). In the latter case, the countries are measured on the scale 0 to 10.0, marking them as authoritarian regimes (0–4.0), hybrid regimes (4.0–6.0), flawed democracies (6.0–8.0), and full democracies (8.0–10.0). The results of the regression analysis are presented below:

A reasonably strong correlation does exist indicating that the ability of a country to innovate correlates with the level of political freedom in this country.

A careful examination of the graph reveals, however, a certain degree of “non-linearity,” implying other factors affecting the innovation index. I’ll delve into this issue in follow-up posts.

But for now, let’s just state aloud what we always intuitively knew: to be more innovative, you should live in a free country.

Check out my eBook, “We the People of the Crowd…,” a collection of stories about crowdsourcing reflecting my personal experience in working with corporate and nonprofit clients.

 Image created by Tatiana Ivanov

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Freedom to Connect

Social media were once considered a liberating technology, a level playing field allowing civil groups and ordinary citizens to reach large audiences at little or no cost. Unfortunately, the open and almost unregulated space of social media platforms has been hijacked by repressive regimes and politicians with authoritarian ambitions, who started to use them as instruments for political distortion and societal control, as tools for surveillance, oppression, and electoral manipulation.

As a result, social media are in crisis. This is a sentiment expressed in a recent report, “Freedom on the Net 2019,” prepared by Freedom House, a non-governmental organization promoting democracy, political freedom, and human rights around the world. The report assessed internet freedom in 65 countries, covering 87 percent of the world’s internet users, and concluded that global internet freedom declined for the ninth consecutive year in 2019.

A few numbers from the report are worth repeating here. Of 3.8 billion people with access to the internet:

  • 65% live in countries where individuals have been attacked or killed for their online activities.
  • 59% live in countries where authorities manipulate online discussions.
  • 46% live in countries where authorities disconnected the internet, often for political reasons.

The report also provided a country-by-country ranking of internet and digital media freedom. Each country received a numerical score from 100 (the freest) to 0 (the least free), which served to mark the countries as Free (700–100 points), Partly Free (40–69 points), or Not Free (0–39 points). Of 65 countries surveyed, 15 (23%) turned to be Free, 29 (45%) Partly Free, and 21 (32%) Not Free.

Among the countries in the Free category, I immediately spotted Iceland, Canada, and France, three established, mature democracies. On the opposite side of the spectrum, in the Not Free category, my eye caught the names of China, Russia, and Iran, all known for their repressive and authoritarian nature. Is there a correlation between having internet freedom and being a free country?

To see whether my observation had any statistical basis, I ran a linear regression test plotting the internet freedom rankings (Y-axis) against Freedom Rating provided by the same Freedom House (X-axis). The Freedom Rating ranks a country’s political rights and civil liberties on the scale 1.0 to 7.0, marking countries as politically Free (1.0 to 2.5), Partly Free (3.0 to 5.0), or Not Free (5.5 to 7.0). The results of the test shown below clearly point to a strong correlation between the two indexes:

There is one potential problem with the above test. One might argue that the observed correlation is exaggerated because both sets of scores are provided by the same source, so that Freedom House gives higher internet freedom scores to the countries it considers more democratic, resulting in a bias.

To exclude such a bias, I repeated the test using as X-axis input the political freedom rankings taken from the Democracy Index 2019 composed by the Economist Intelligence Unit. In the latter case, the countries are ranked on the scale 0 to 10.0, marking them as authoritarian regimes (0–4.0), hybrid regimes (4.0–6.0), flawed democracies (6.0–8.0), and full democracies (8.0–10.0).

The resulting plot is shown below (please note that the inverted slope of the curve is because the Economist Intelligence Unit ranks political freedom in ascending order while Freedom House in descending):

A strong correlation between the two indexes was evident again leading to the conclusion that the more democratic a country is, the more internet freedom it provides to its citizens.

This is a hardly surprising discovery because it only confirms what we’ve intuitively known for a long time.

Want a free internet? Live in a free country!

Check out my eBook, “We the People of the Crowd…,” a collection of stories about crowdsourcing reflecting my personal experience in working with corporate and nonprofit clients.

 Image provided by Tatiana Ivanov


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On Steve Jobs, Henry Ford, and Fast Horses

A solid consensus seems to exist that customer feedback, gathered through market research, is a key to successful innovation. And yet, I’m surprised how often one can hear dissenting voices. Some folks, especially not engaged in day-to-day innovation activities, claim that paying too much attention to customers can stifle innovation, degrade it to a mere incremental improvement of existing products (which these folks consider as anathema to the “true” innovation).

In support of their position, they routinely quote Steve Jobs: “It’s really hard to design products by focus groups. A lot of times, people don’t know what they want until you show it to them.” A plausible interpretation of this quote would seem to be that had Jobs listened to his customers, Apple would still have been making incremental improvements to Apple-1.

Another supportive line to the same argument is attributed to Henry Ford: “If I had asked my customers what they wanted they would have said a faster horse.”

Recently, I came across a brilliant piece by Tristan Kromer, who provided an interesting twist to Ford’s line:

“If the customer asks for a faster horse, do not build a faster horse. Ask, “Why do you want a faster horse? What would you use it for?” If the customer wants a faster horse to move cargo across town, a car might be a great invention. When the customer wants a faster horse to win a horse race, a car is a terrible invention.”

And then it struck me. I reread Ford’s quote. Read it again, too: “If I had asked…they would have said.”

Ford didn’t ask his customers! He simply assumed that all they wanted was a faster horse. But he invented the car instead – and good for him!

It’s still unfortunate that Ford didn’t develop a habit of asking his customers what they wanted. I doubt that many of them would have said they wanted a faster horse. Most of them would have replied, as Tristan Kromer suggested, that they needed to move cargo across town. And if Ford kept asking follow-up questions – which cargo quantities, for which distances, at which speed – useful feedback would have inevitably emerged. Who knows, had Ford had a habit of talking to his customers, the first Ford truck – arguably the best Ford Motor Company’s invention ever – would have been invented earlier than 20 years after the first Ford car.

Curiously, in the 1930s, the Toyota Motor Corporation invented 5Y (the 5 Whys technique), a simple but powerful approach to get employee and customer feedback. I don’t want to sound preposterous but had Ford, not Toyota, invented 5Y, it could have been Ford, not Toyota, occupying today the top spot on the list of the biggest car manufacturers in the world.

Of course, one should understand the difference between two related, overlapping, yet distinct forms of customer feedback: customer wants and customer needs. What focus groups produce is the customer wants: a demand for a faster horse or a faster computer. It takes more time and effort – and much more sophisticated market research tools – to identify customer needs behind customer wants. True, people often don’t know that they want a product until you show it to them. But it is only after they realized that they needed this product – and wanted it too! -that they would be ready to pay for it. There is no innovation without customer feedback – either in the form of wants or needs.

And what about Steve Jobs? Read his quote again, too. Jobs obviously didn’t like focus groups, arguably a very messy tool of collecting consumer feedback. His quote says nothing about other forms of market research. Did he detest them all? I don’t know.

Regardless, a genius like Steve Jobs can afford to eschew proper market research and trust his guts. Feel yourself on par with Jobs? Go ahead and try! Just don’t be surprised if your innovation journey won’t be as successful as Apple’s.

Check out my eBook, “We the People of the Crowd…,” a collection of stories about crowdsourcing reflecting my personal experience in working with corporate and nonprofit clients.

Image credit: Photo by Gene Devine on Unsplash

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United by technology, separated by ideology?

A 2017 Pew Research Center study reported that 41 percent of Americans had experienced online harassment, an increase from 2014. A more recent survey by the Anti-Defamation League showed that already more than half of Americans, 53 percent, say they experienced hate speech and harassment online in 2018.

What is going on? Why is the internet being inundated with harmful content? What is the origin of the problem and can we develop solutions to solve it?

To start sorting out this important topic, HeroX, a leading crowdsourcing platform, spoke with Jesse McCrosky, Sr. Data Scientist at Mozilla. Jesse is interested in the ethical dimension of the use of big data and the ways it may influence our societies.

Read the transcript of the interview here, but I also strongly recommend listening to the original audio version of the interview to fully benefit from Jesse’s knowledge and experience. Also, visit Jesse’s blog “Wrong, but useful” to get more insight into the problem.

I’d like to highlight a quote from the interview:

“The technology isn’t inherently evil, but people should be conscious of what they are doing and what content they’re consuming …. [R]emember that harmful content is first and foremost a social, not technical, problem. It reflects the divisiveness of our societies. As a society, we must learn to be sympathetic and compassionate and try to understand even people we disagree with. And this is the best way to fight back what has been done to us through technology.”

Very well said, Jesse!

Check out my eBook, “We the People of the Crowd…,” a collection of stories about crowdsourcing reflecting my personal experience in working with corporate and nonprofit clients.

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The Words We Choose

In a recent HBR article “Stop Calling It Innovation,” Nadya Zhexembayeva suggests ditching the term “innovation.” Her point? Employees hate innovation. Rightly or wrongly, they associate innovation with undue risk, extra work without reward, and even job loss. As a result, Prof. Zhexembayeva argues, they tend to avoid corporate innovation activities at all.

I agree with Prof. Zhexembayeva that employees hate certain things. I, however, doubt that changing the terminology alone will achieve much. Everyone hates being reprimanded by their manager but did replacing “negative feedback” with “constructive” help? Or, for that matter, will replacing “lay-offs” with “workforce reduction” or “downsizing” help alleviate the pain of being terminated?

(As a side note, there is a lot of talks these days that the future developments in Artificial Intelligence may result in a massive loss of jobs – and many employees are apprehensive about it. Isn’t it time to rename AI into something else? “Non-human cognition,” perhaps?)

Prof. Zhexembayeva’s attempt to solve corporate innovation problems with terminological fixes isn’t without precedent. Back in 2016, Stefan Lindegaard, too, called for trashing the term “innovation” and replacing it with “transformation.” (Lindegaard also suggested to get rid of the term “Chief Innovation Officer” in favor of “Chief Digital Officer.”) And later, Scott Kirsner advocated eliminating the term “corporate entrepreneur” because, in Kirsner’s opinion, this term was obstructing, rather than facilitating, corporate innovation.

I’m not against changing terminology in principle. The business environment rapidly evolves, and our mental and verbal constructs must reflect that. The critical issue, though, is whether the new term works better than the incumbent.

And this is, in my opinion, the weakest point in Prof. Zhexembayeva’s terminology upheaval. In fact, she doesn’t propose any real replacement to “innovation” except for mentioning that a couple of her clients used verbal constructs including the words “idea” and “reinvention.”

Does Prof. Zhexembayeva really imply that “idea” and “innovation” are the same thing? True, innovation starts with collecting ideas, which are then assessed, validated, tested, and finally implemented into new products, services, and operational improvements. Ignoring this all-important implementation part of the innovation process, the one that follows the ideation part, simply means a misrepresentation of what innovation really is.

Yes, there is no innovation without ideas. But the reverse isn’t true as evidenced by numerous examples of organizations collecting zillions of poorly defined “ideas” (usually during hackathons and other “idea-generating” exercises) and not knowing what to do with them.

I’d argue, however provocatively that might sound, that the periodic calls to ditch the term “innovation” reflect a sort of intellectual cowardice on the part of the corporate innovation leadership. Our corporate innovation leaders often do a very poor job in defining what innovation means specifically for their organizations. Innovation charters, a formal document outlining the major aspects of the organization’s innovation strategy, are almost unheard of. Attempts to introduce portfolio management of innovation projects are often met with a deadly fire because “structure” supposedly kills innovation. A simple idea that for each innovation objective there must be a specific innovation tool most suited for this objective, sounds almost foreign.

And on top of that, corporate innovation leaders fail to explain to their employees that today, innovation isn’t a luxury, not even a dispensable corporate function. It’s the only way to survive – for their organizations and employees alike.

Why bother? Let’s stop calling it innovation instead.

As I wrote just a few weeks ago, it falls on all of us – academics, business writers, and innovation practitioners – to educate corporate leaders and their employees on the very basics of innovation: definitions, typology, infrastructure, processes, metrics, and incentives. We need to create a set of short narratives (“Innovation101,” so to speak) giving organizations a place to start, in a practical and intuitive way.

No one will do that if we don’t. So, let’s do that and leave the fun of playing with words to creative writers.

Check out my eBook, “We the People of the Crowd…,” a collection of stories about crowdsourcing reflecting my personal experience in working with corporate and nonprofit clients.

 Image provided by Tatiana Ivanov

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United We Innovate

As I wrote on numerous occasions, in recent years crowdsourcing has become a popular topic in academic circles, business publications, and social media. Yet, its acceptance as a practical problem-solving tool has been relatively slow.

There are a few reasons for the slow adoption of this potentially powerful open innovation tool (see, for example, here and here). One of them is a huge number of different crowdsourcing platforms available in the marketplace, with some experts putting this number at 1,000 worldwide.

Obviously, navigating such an ocean of different options is challenging, to say the very least, especially for the organizations new to crowdsourcing. Mistakes are quite often in matching problems organizations want to crowdsource to platforms best suited to deal with each specific problem.

Do we really need a thousand different crowdsourcing platforms? Hardly. In fact, many of them appear and rapidly disappear without leaving any tangible record of performance. Besides, even the platforms that are still in business often do an awful job of differentiating themselves from others.

What is also puzzling is that there is almost no M&A activity in this space. As far as I remember, the only known M&A case involving a crowdsourcing platform was the 2018 Planview’s purchase of Spigit, a developer of innovation management software. And back in 2015, IdeaConnection, an open innovation service provider, and Brightidea, another developer of innovation management software, announced that they had formed a technology and services “partnership.”

The partnership between IdeaConnection and Brightidea, while no formal M&A, was a step in the right direction. Creating a one-stop-shop of innovation services could potentially help organizations launch their open innovation initiatives without the agony of going through an oversized toolbox of almost identical tools. Such partnerships could also emphasize the urgent need for consolidating internal corporate innovation programs with external (open) innovation activities.

It appears that the idea of forming “partnerships” between innovation service providers is gaining traction. Last December, a popular crowdsourcing platform HeroX signed a strategic partnership agreement with Ideanco to launch two challenges focused on climate change and food security. The partnership will also help develop startups incubated within the Ideanco Innovation Lab.

And just a few days ago, a veteran of the open innovation movement InnoCentive has signed a major partnership with the UK idea management company Wazoku with a purpose to create the world’s most comprehensive open innovation platform. The partnership is expected to integrate Wazoku’s Idea Spotlight innovation platform with InnoCentive’s global network of more than 400,000 expert problem “solvers.” Announcing the partnership, Alpheus Bingham, CEO and co-founder of InnoCentive, has specifically mentioned customer demand for “integrated offerings.”

It remains to be seen whether any of the established “partnerships” evolve in something more formal. However, the very trend of consolidating available open innovation services looks very attractive.

Check out my eBook, “We the People of the Crowd…,” a collection of stories about crowdsourcing reflecting my personal experience in working with corporate and nonprofit clients.

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The “French perfume” innovation

(This post originally appeared on Medium)

I grew up in the Soviet Union and know a thing or two about the shortage of goods. The perennial chasing of hard-to-get stuff had instilled in me and my compatriots one simple habit: buy something first, while it’s still available, and then decide whether you need this something or not. This approach was especially useful for imported items, which were rarer and even more difficult to size up.

One such item was “French perfume.” I’m using quotation marks here because when buying a precious bottle – on the black market or through a friendly connection – one didn’t have the luxury to know the brand of the future acquisition. It was just it, a bottle of “French perfume.” Pondering if the intended receiver of the item, your wife or girlfriend, would have preferred Chanel, Guerlain, or Magie Noire, was completely pointless: you could buy only what you were given. On the positive side, your loved one wouldn’t care; she would just be delighted with the gift.  She would also appreciate your effort to please her – and proud of your ability to get things done.

Today’s corporate innovation reminds me of this “French perfume.”

Volumes have been written by Ralph-Christian Ohr and others about the 3-Horizon Model of Innovation that places innovation projects into incremental, “adjacent,” and transformational buckets, each bucket implying a different time horizon and funding level. A complementary, equally useful, classification of corporate innovation projects into market-creating, sustaining, and efficiency innovations – each corresponding to a specific stage of business model development – was proposed by the late Clay Christensen and his colleagues.

And yet, time and again, our corporate innovation leaders can’t provide a working definition of what innovation means for their organizations. It’s just it, “innovation.” Innovation charters, a formal document outlining the major aspects of the organization’s innovation strategy, are almost unheard of. Attempts to introduce portfolio management of innovation projects are often met with a deadly fire because “structure” supposedly kills innovation. Worse, many corporate innovators sincerely believe that every innovation must be “disruptive” while all other types of it are for losers.

The lack of understanding of the various types of innovation inevitably leads to confusion about the available innovation tools. A simple idea that for each innovation objective there must be a specific innovation tool most suited for this objective, sounds almost foreign. Instead, one-size-fits-all fads follow each other like ocean waves hitting the innovation process shoreline – hackathons, skunkworks, innovation labs, corporate accelerators, corporate venture funds – with inevitable complaints of low innovation returns later. “Idea generation” campaigns are omnipresent, confusing minds, draining resources, frustrating participants, and resulting in pretty much nothing.

Steve Blank has a perfect definition for our corporate innovation process: innovation theater – and I humbly hope that my own term, “the French perfume innovation,” will become as popular as Blank’s.

What is to be done? My solution is simple, if not quite revolutionary: education. We need to get back to the drawing board and help organizations understand the very basics of innovation: definitions, typology, infrastructure, processes, metrics, and incentives. We need to create a set of short narratives (“Innovation101,” so to speak) giving organizations a place to start, in a practical and intuitive way.

No, I’m not calling on academics to stop deepening our scientific understanding of the innovation process. I’m urging them not to forget that by leaving behind knowledge that the innovation practitioners can’t use they make their further work less meaningful. Nor am I saying that the “new models of innovation” are completely useless. What I’m saying is let’s learn what we already have first.

Check out my eBook, “We the People of the Crowd…,” a collection of stories about crowdsourcing reflecting my personal experience in working with corporate and nonprofit clients.

Image provided by Tatiana Ivanov

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Detecting cancer in a-intelligent way

Good news from the front lines of the War on Cancer. The American Cancer Society reported the sharpest drop in cancer death rates in the United States between 2016 and 2017. The 2.2% drop, the biggest single-year drop on record, seems to be driven by accelerating declines in mortality from lung cancer, the leading cause of cancer death in the U.S.

The decline is attributed to two major causes: reduction in smoking, the biggest risk factor for lung cancer, and the development of new cancer treatments.

The ACS report also touches upon one of the bumpiest corners of the cancer field: cancer screening. Many diagnostic tests do identify cancers early when treatment is usually more effective. But they also identify growths that would never turn deadly – a phenomenon called “overdiagnosis.”

Many experts hope that further improvements in the efficiency of cancer screening can be achieved using advances in Artificial Intelligence. Two recent studies lend credit to this hope.

In the first study, a joint team of British and U.S. researchers trained an AI system to identify breast cancers using a set of ~29,000 mammograms. The authors of the study then showed that AI was able to identify cancers at least with a similar level of accuracy – and even higher in a separate experiment – as expert radiologists. Moreover, using the AI system allowed to reduce, by a few percent, the number of false-positive and false-negative results.

In the second study, conducted by a diversified team of U.S. scientists and clinicians, an AI system was fed with 2.5 million labeled samples of brain cancer biopsies and taught to identify 13 different types of brain cancer. In a side-by-side comparison, the AI system needed less than 150 seconds to make a diagnosis (as compared to about 30 minutes for a neuropathologist), with the accuracy being at least equal to that of a human tester (94.6% and 93.9%, respectively). Interestingly, the human testers were able to correctly identify samples AI could not and, vice versa, AI was able to identify samples the human testers diagnosed incorrectly.

Both studies imply that combining human testing with AI-assisted one can dramatically speed up the process of cancer screening while at the very minimum preserving the accuracy of testing.

Do we have bad news? Yes, we do. It will take years until the AI diagnostic systems become a mainstream of medical practice as large-scale clinical trials are required to get the green light from regulatory authorities.


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Computational propaganda: another dark corner of the net

Sir Tim Berners-Lee has all the reason to be proud of his life’s crown achievement: the World Wide Web. But he is not. In a series of interviews last fall, Berners-Lee complained that the internet today isn’t what he imagined almost 30 years ago when he invented it. In a long list of specific concerns, Berners-Lee mentioned the pervasiveness of ads, privacy breaches, hate speech, and fake news.

A recent report documents the rise and rapid maturation of yet another troublesome net tool: organized social media manipulation or computational propaganda, in the words of the report’s authors, Samantha Bradshaw and Philip N. Howard of the University of Oxford.

Bradshaw and Howard argue that computational propaganda, which they define as “the use of algorithms, automation, and big data to shape public life,” is becoming a pervasive and ubiquitous part of everyday life. Its presence can be spotted in 70 countries, up from 48 countries in 2018 and 28 countries in 2017.

The most troubling techniques of computational propaganda include the use of “political bots” to amplify hate speech or other forms of manipulated content, the illegal collection of data and micro-targeting, and deploying of trolls to bully or harass political opponents or journalists. Seven countries – China, India, Iran, Pakistan, Russia, Saudi Arabia, and Venezuela – have also used computational propaganda to influence political events in foreign countries.

Even nations not known for the aggressive weaponizing of the net take advantage of some “mild” forms of computational propaganda. For example, in Germany and Sweden, political parties and/or non-government entities use social media manipulation to advance political and social causes.

Facebook remains the most popular platform for social media manipulation, with some evidence of computational propaganda campaigns on Facebook found in 56 countries. At the same time, the increased use of YouTube, Instagram, and WhatsApp has also been reported.

The usage of human-operated social media accounts is still the most popular way of conducting computational propaganda: 60 out of the 70 countries use them. Bot accounts come next, with 50 out of 70 countries employing bot accounts. Of special concerns is the use of stolen or hacked accounts to conduct social media manipulation campaigns. Five countries – Guatemala, Iran, North Korea, Russia, and Uzbekistan – have been marked for this type of behavior.

In the United States, social media manipulation is actively used by government agencies, private contractors, and to a lesser extent, political parties. Human, bot, and cyborg (a blend of automation with human curation) accounts are being employed. There is no evidence of the United States’ use of computational propaganda in foreign countries; however, it was reported that a fake social network in Cuba had been created by the USAID.

The current spread of computational propaganda, as troubled as it already appears, is obviously just a beginning. Its further growth and maturation will be augmented by new technologies, such as AI, VR, and IoT. Eventually, countries and societies will have to deal with this phenomenon. Unfortunately, there are no signs that it’ll happen any time soon.


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