Tag: Google

The Big Data Value Chain

There are three types of company in the big-data value chain: the companies who collect the data, data-analytics companies, and data-ideas companies. This new ‘organisational landscape’ will change the power-relations between businesses enormously, at least according to Viktor Mayer-Schonberger and Kenneth Cukier (2017)  in ‘Big Data’: The Essential Guide to Life and Learning in the Age of Insight;. 

‘Pure’ data companies are those which have the data, or at least access to it, but not necessarily have the right skills to extract the value from the data. A good example of such a company is Twitter, which has masses of data but licences it out to independent firms to use.

Data analytics companies are those with the statistical, programming, and communication skills necessary to mining insights from data – Teradata is a good exmaple of such a company.

Finally there are those companies with the ‘big-data mindset’ whose founders and employees have unique ideas about how to unlock and combine data to find new forms of value – for example, Pete Warden, the co-founder of Jetpac, which makes travel recommendations based on the photos users upload to the site.

Data analytics has recently been touted as being in the ‘prime position’ in the big-data value chain: there has been a lot of recent talk of the shortage of ‘data scientists’ in the age of ever increasing amount of data…. The McKinsey Global Institute has talked about this for example, and Google’s chief economist Hal Varian famously called statistician the ‘sexist job around’.

We have been given the impression that we are wallowing in data, but lack sufficient people with the skills to mine this data.

Cukier, however, thinks such claims are exaggerated because it is likely that this skills gap will close. Interestingly, in a recent talk on big data science, this view also seemed to be the consensus.

He predicts that what is more likely to happen is that firms controlling access to the data will start to charge more for it, and big data innovators will be be where the real money is…

Hyrbid Data Companies

Companies such as Google and Amazon stretch across all three links in the data value chain. Google collects data like search-query typos, uses it to create a spell-checker and employs people in-house to do the analytics. Such vertical integration is no doubt precisely why Google is today one of the world’s largest companies.

The New Data Intermediaries

Cukier also predicts that there are certain business sectors which will benefit from giving their data to third parties, because keeping it in-house will not be as beneficial to them as sharing their data and combining it with others – third parties are needed to facilitate trust – for example, travel firms will benefit from such an arrangement, not to mention the banking and finance sectors – where more data is better.

The Demise of the Expert

Cukier also predicts that big data analytics will see specialists in different fields being replaced with those with data-science skills able to manage whatever field based on data. He argues that ‘mathematics, statistics, perhaps with a sprinkling of programming and network science, will be as foundational to the modern workplace as numeracy was a century ago and literacy before that’.

Big Winners, Medium Sized Losers..

Large data companies such as Google and Amazon will continue to soar, but big data presents a challenge to the victors of small-world data such as Walmart, Nestle, Boeing…. How these will adapt remains to be seen.

There are, of course, opportunities for ‘smart and nimble start-ups’, but also individuals might start to sell their own data, possibly through new third party firms.

What is Big Data?

Big data refers to things one can do at a large scale that cannot be done at a smaller scale. Big data analysis typically uses all available information and billions of data points to identify correlations which reveal new insights about human behaviour which are simply not available when using smaller data sets.

What is Big Data.png

Big data has emerged with the widespread digitisation of information which has made it easier to store and process the increasing volume of information available to us.

Big data is also dependent on the emergence of new data processing tools such as Hadoop which are not based on the rigid hierarchies of the ‘analogue’ age, in which data was typically collected with specific purposes in mind. The rise of big data is likely to continue given that society is increasingly engaged in a process of ‘datification’ – there is an ongoing process of companies collecting data about all things under the sun.

Big data is also fundamentally related to the rise of large information technology companies, most obviously Google, Facebook and Amazon, who collect huge volumes of data and see that data as having an economic value.

A good example of ‘big data analysis’ is Google’s use of its search data to predict the spread of the H1N1 flue virus in 2009, based on the billions of  search queries which it receives every day. They took 50 million of the most search terms and compared them with CDC (Centre for Disease Control) data, and found 45 search terms which were correlated with the official figures on the spread of flu.

As a result, Google was able to tell how the H1N1 virus was spreading in real time in 2009 without relying on the reporting-lag which came with CDC data, which is based on people visiting doctors to report flu, a method which can only tell us about the spread of flu some days after it has already spread.

A second useful example is Oren Etzioni’s ‘Farecast company’ – which evolved to use 200 billion flight-price records to predict when the best time for consumers would be to buy plane tickets. The technology he evolved to crunch the data today forms the basis of sites such as Expedia.

There are three shifts in information analysis that occur with Big Data

  1. Big data analysts seek to use all available data rather than relying on sampling. This is especially useful for gaining insights into niche subcategories.
  2. Big data analysts give up on exactitude at the micro level to gain insight at the macro level – they look for the general direction rather than measuring exactly down to the single penny or inch.
  3. Big data analysis looks for correlations, not causation – it can tell us that something is happening rather than why it is happening.

Cukier uses two analogies to emphasise the differences of working with big data compared to the ‘sampled data’ approach of the analogue age.

Firstly, he likens it the shift from painting as a form of representation to movies – the later is fundamentally different to a still painting.

Secondly, he likens it to the fact that at the subatomic level materials act differently to how they do at the atomic level – a whole new system of laws seem to work at the micro level.

Big Data – don’t forget to be sceptical! 

This post is only intended to provide a simple, starting point definition of big data, and the above summary  is taken from a best selling book on big data (source below) – this book is very pro-big data – extremely biased, overwhelmingly in favour of it – if you buy it and read it, keep this in mind! Big data also has its critics, but more of that later.

Sources

Based on chapter 1 of ‘Mayer-Schonberger and Cuker (2017) Big Data: The Essential Guide to Work, Life and Learning in the Age of Insight’.

 

The ‘Postmodern’ Tech Companies Embarking on ‘Modernist’ Projects

Technology Transnationals such as Apple, Google and Facebook have effectively embedded themselves into the lifeworlds of billions of people the world over through weaving their products and services into the fabric of daily life.

While in many ways these tech firms are quintessentially postmodern, there are some ways in which they seem to harken back to the modernist era.

Firstly, some of these tech giants are employing top architects to build massive buildings for them, spectacular symbols of their immense global power. While the design of these buildings is ‘obviously’ (?) postmodern, personally I think the sheer scale, cost, and the ultimate profitability-function of them  screams ‘modernism’.

The building that commands the most attention is the Apple/ Foster circle – so big that it’s said to be visible from space. It’s built on 150 acres, and is designed to cater for 12 000 workers. It’s something like a permanently landed space ship with a garden area in the middle.

Inside this building, you’ll discover a world of whiteness, greenery and silver, with a 100 000 square foot cinema, a cafe that can serve 4000 at once, which has sliding class doors 4 stories high, each weighing nearly 200 tonnes.

There is also a 1000 seat Steve Jobs cinema, surmounted by a 165 ft wide glass cylinder, for Apple’s famous product launches, and with a landscape designed to emulate a national park.

The doorways have perfectly flat thresholds because, according to a construction manager reported by Reuters, ‘if engineers had to adjust their gait when entering the building, they risked distraction from their work’.

Writing in the Financial Times, George Hammond also suggests that Facebook is ‘going back to the 19th Century’, more evidence of the modernist turn these postmodern companies are taking….

Facebook us trying to combat soaring rents in Silicon Valley by building new houses, which marks a revival of the 19th century concept of the ‘company town’: its new Willow Campus includes plans for 15% of the 15000 houses to be made available at below market rates, for example.

Hammond is sceptical about whether such a scheme will work, noting that there was a mixed record of success in the 19th century – Cadbury’s Bournville in Birmingham dramatically improved conditions for workers, but Henry Ford’s Fordlandia in Brazil was a spectacular failure.

Whether these massive-buildings and ‘city projects’ are successful or not, they certainly demonstrate the huge power these companies have alter the physical environment in which we work and live in addition to their power to influence the way we access information.

What next for Corporate Power? 

Sources:

The Week (5 August 2017 and 29 July 2017)

 

Technology Companies and the Digital Privatisation of Public Education

Education has long been influenced by private companies, but the rise of digital education has expanded the role of private technology companies, in public education enormously. Such companies range from the big global technology companies such as Microsoft and Facebook to smaller, silicon valley tech startups.

This post explores the companies involved, and the neoliberal, Silicon Valley mindset that lies behind what I call the ‘digital privatization of public education’.

Introduction – Digital Capitalism and Education

Schooling in the 1700s and 1800s was provided largely through private institutions, and the expansion of public education in the late 19th and 20th centuries was influenced by the commercial interests of text book publishing companies.

Digital Technology gives private, commercial interests greater potential to influence how public education is organised and delivered.

The reason for this is simply logistical – Nation States do not have the scope to develop digital technologies, and so it is massive, Transnational private technology companies such as Facebook, Google, Apple and Microsoft which are  driving the development of these technologies, and the public education sectors of national governments who are their largest potential market.

All of the above mentioned companies have education divisions, oriented to developing education software and applications for use in schools, and many other companies are developing educational products: from Pearsons to Lego.

At the other end of the scale from the massive TNC sector there are hundreds, if not thousands of smaller educational technology start ups, as small-fish seek to gain a foothold in the education market.

The fact that digital education is very big business is due to the fact that the global market for education is estimated to be around $5 trillion, with the estimated market for online Higher Education ‘e-learning’ products alone estimated at $91 billion.

In short, the potential expansion of for-profit digital education is huge.

The benefits of commercial involvement in digital education

Selwyn identifies a number of (potential) benefits of the involvement of private ICT companies in bringing digital technology more into public education:

  1. TNCs enjoy economies of scale that dwarf public sector organisations – they have global reach, and enormous sums of money to invest, and they tend to ‘think big’… as one of Google’s international heads of education puts it: ‘Technology was hard to deploy in schools and we’re making the solutions we supply very easy to manage….new technology is finally able to work for us in schools’.
  2. The private sector emphasize the importance of quick results and demonstrable outcomes – they are, after all, ultimately accountable to their share holders.
  3. The IT industry is clearly well poised to bring innovation into education – innovation being defined as introducing new products and ideas that support changes in the established way of doing things. These organisations thrive on thinking big and acting quickly. They pride themselves on thinking differently – they see themselves as risk takers and boundary-pushers, cultivating an ‘outsider perspective’ unfettered by establishment thinking or old money. This is especially true in the ed-tech start-up sector, in which millions of dollars are invested in hundreds of companies, only a few of which will go on to be the next ‘big thing’.

Digital Education and rise of ‘Californian Capitalism’

Sebastian Thrun (co-founder of online learning company Udacity Inc reasoned ‘Education is broken. Face it…. it is so broken at so many ends, it requires an little bit of Silicon Valley Magic’.

The idea of ‘Silicon Valley Magic’ alludes to the set of business practices and approaches that underpin the new high-tech economy and its increased interest in education.

This mentality was described neatly by Will Hutton, based on his account of a visit to Palo Alto during the early 2010s following which he wrote of the global significance of the strain of ‘Californian Capitalism’ that characterizes Silicon Valley institutions such as Google, Oracle and even Stanford University.

‘We are increasingly living in a world where economics, politics, culture and society are being shaped by West Coast ideals of the power of computing, entrepreneurialism and risk-taking approach to investment.

The ways Silicon Valley firms seek to do business are shaped profoundly by the programming and hacking backgrounds of their main protagonists such as Mark Zuckerberg, Larry Page, Sergcy Brin, Larry Ellision, Peter Thiel and so on. All of these high-tech billionnaires remain steeped in a programmer mindset where a faith in computational power and an always on networked way of life fuel a relentless focus on invention and innovation.

This is a culture of all night coding sessions and a succession of ambitiouss start-ups, most of which quickly fail, backed by investors keen to take a punt on the next ‘big thing’.

These are ventures which are based on big ideas, solving computational problems, entrepreneurialism, openness, collaboration, learning through failure and relentless self belief and optimism, based on a relentless mindset that revels in the power of individuals rather than institutions, and the creative potential of manageable amounts of renewal and disruption.

Although all of these high tech firms seek to make a profit, many of the main industry protagonists also want to ‘make a difference’ and seek to use frontier technologies to engage with immense societal challenges such as world health and global poverty, and it understands that it is part of society and owes a debt to the culture and public infrastructure that created it.

Thinking Big, spending bigger

Education is one of those sectors in which silicon valley firms seek to ‘make a difference’. This is evidenced in many different forms:

In the well-established and vast educational programmes run by all of the large multinational IT companies – often under the aegis of ‘corporate social responsibility’. These activities range from the physical design and construction of ‘schools of the future’ to the development of teacher training programmes, alternative curricula and the provision of computer hardware, software and the infrastructure to educational institutions.

There are also a range of far more ambitious initiatives such as Peter Thiel’s ‘Thiel Fellowship’ through which young people are awarded $100 00 to drop out of college and pursue their dreams by setting up a world changing business idea’; Mark Zukerberg’s ‘Start-up: Education’ through which Zuckerberg has made personal donations of $100 million to the Newark school district and $120 million to schools in the Sanfrancisco Bay area; the Bill and Melinda Gates Foundation boasts an extensive educational programme, including its key role in driving recent US school reforms around standardised testing and the common core curriculum. It has also spent over $470 million on US higher education reform, funding projects and generally creating what the Chronicle of Higher Education calls an ‘echo chamber of like minded ideas’.

We should also not overlook the considerable ‘soft power’ of high tech corporations in education decision making, such as with the computer industry’s considerable lobbying governments to focus more on teaching coding in schools, which now seems to be accepted universally as a ‘good thing’. The Chairman of Google, Eric Smidt has been a leading proponent of this push since 2010.

Finally, there are the various companies involved in setting up MOOCs, one of the largest of which is Coursera, bolstered by $85 million of venture capital funding.

All of these activities shows that corporate involvement in education is sometimes submerged in complex networks of influence and power, and if one finds time to follow the money, one finds that high-tech firms are in some way involved in seeking to profit from most, if not all, of the digital education initiatives out there.

It follows that the biggest movers and shakers in digital education are not educators and teachers, but rather programmers, hackers and the trillion dollar tech industry which has grown up around them.

These interventions illustrate the power which IT corporations can wield over public education, and these are increasingly strong voices in conversations about education reform, setting the tone for how education should be reimagined in the ‘digital age’.

Sources: Nick Selwyn (2016): Is Digital Education Good for Education?

Forthcoming Post:

The problems of the increasing role of Tech companies in public education

 

 

 

 

 

How Technology Companies Manipulate our Behaviour

Design features such as likes, swipes, notifications and autoplays make being on-line more addictive, less autonomous, and cause pyschological and social harm, at least according to this recent Guardian Article by Paul Lewis: Our minds can be hijacked: the tech insiders who fear a smartphone dystopia‘.

Are we all digital technology zombies?

Below I summarize this article and add in a few comments.

Technology companies such as Apple, Facebook and Google have incorporated a range of design features into their mobile devices, operating systems and social media applications that make them addictive, which results in us spending longer online than we really want to, clicking on links we never intended to and making us more distracted, less rational and more impulsive than ever.

Former Google employee Tristan Harris says that all of our minds are “jacked into the system” and “all our minds can be hijacked. We are not as free as we think we are”. Harris believes that tech companies deliberately set out to make their products addictive, as they are oriented to respond to the incentives of an advertising economy and thus experiment with techniques which are most likely to grab people’s attention.

As an example, Harris points out that the Facebook icon which notifies users of new activity and ‘likes’ was originally blue, but no one used it, then they switched it to red, and everyone used it, because red is a trigger colour, which is why it is used as an alarm signal. Now the red icon is everywhere, and every time smartphone users glance at their phones, dozens or hundreds of times a day, they are confronted with small red dots, pleading to be tapped.

red notification icon
The Red Notification Icon – Inducing the anxiety of variable rewards?

The most seductive design, according to Harris, exploits the psychological susceptibility that makes gambling so compulsive – variable rewards. Each time you swipe down you don’t know what’s coming next, either an avalanche of likes, or nothing, and the action even mirrors that of the slot machine: a human action to ‘pull down’, and a pause before a variable result. The pull-down to refresh was originally designed in 2009, and has since become one of the most widely emulated features in apps – even though refreshing can now be done automatically, the pull-down function remains, because if users aren’t involved in the process, then the experience is less addictive.

social media swipe addiction
Swipe to refresh and lock-in your addiction

Justin Rosenstein designed the like feature for Facebook in 2007 – to create a means to send ‘little bits of positivity at the click of a button’, creating what he now calls ‘bright dings of pseudo-pleasure’. ‘Likes’ were  wildly successful, and hence they spread to a range of other social media platforms, and now it is the short-term pleasure of this social affirmation that is one of the features which drives people to touch, swipe or tap their phone more than 2500 times a day on average.

Facebook Like
Facebook like – dings of pseudo-pleasure?

Tech companies can exploit such information to keep people hooked: manipulating, for example, when people receive ‘likes’ for their posts, ensuring that they arrive when an individual is most likely to feel vulnerable, or in need of approval, or just bored, and such information can be sold to the highest bidder.

James Williams, a former Google employee who built the metrics system for the company’s global search advertising business, but has now turned critic of the industry, describes the tech industry as one which has the ‘largest and most centralised form of attentional control in human history’ – he had an epiphany moment one day while working at google when he glanced at one of Google’s multi-coloured dashboards showing how much of people’s attention the company had commandeered for advertisers. He says that he realised ‘this is literally a million people that we’ve persuaded to do this thing that they weren’t going to do otherwise.’

Some of the Negatives Effects of Being Online

Firstly, technology may be contributing to so-called ‘continuous partial attention’ – In the attention economy (driven by the needs of advertisers) – everyone is distracted most of the time – which actually prevents us from getting things done, the complete opposite of what technology was intended to do!

Secondly, the attention economy thrives on a ‘sensationalise, bate and entertain’ logic and as a result the media is now is now more than ever biased in favour of that which is sensationalist and entertaining. People like Donald Trump do well in this environment because they are good at grabbing attention with their simplistic,  emotional and extremist views –  that which is rational is less likely to get attention than that which is impulsive.

Finally, and related to the above point, this may be changing how we view politics – we see it in increasingly polarised terms – because the only thing which grabs our attention at a similar level of Donald Trump is a similarly extreme reaction, in the form of Bernie Sanders or Jeremy Corbyn for example.

What are the solutions to avoid getting addicted in the attention economy?

Some of the big names who created the technologies of the attention economy are actually ducking out of it themselves – having turned off their social media updates, or even uninstalled most of the apps from their hardware.

Find out More

If you’re interested in Tristan Harris’ initiative to make digital technologies less addictive – you might like to check out his Time Well Spent Website, and his TED talk below…

Related A-Level Sociology Debates

As I see it this material fits in to at least two places on the A-level sociology syllabus:

  • This material seems to be coming from the structuralist side of sociology – that society shapes (or at least frames) social action. See this post: ‘Sociological perspectives: the basics‘ for an overview of structure versus action approaches in sociology.
  • There’s also some clear relevance to the increasing power of Transnational Corporations: this material certainly suggests that transnational technology companies wield enormous power to shape people’s actions.
  • If you study the media option for A level paper 2, no doubt it’s even more relevant!

 

 

Is Google Sexist?

In a memo published in August 2017 a (male) Google engineer suggested that gender inequality in the technology industry in general and Google in particular is not due to sexism, but due largely to biological differences between men and women.

The memo was called “Google’s Ideological Echo Chamber” and the guy who wrote it was James Danmore. His short answer to the question ‘is Google sexist’ would be ‘no, in fact quite the opposite – Google subscribes to a leftist ideology and actually practices unfair authoritarian discrimination in favor of women over men’.

Google's Ideological Echo Chamber

This memo is a great example of a New Right view on gender inequality – basically that men are naturally (biologically and psychologically) better suited to the demanding, analytical type of jobs that exist necessarily?) in a highly competitive tech industry.

Google CEO Sundar Pichai responded by saying that the memo suggested harmful gender stereotypes and sacked Danmore. Needless to say this whole incident has provoked a strong response from both the left and the right.

All I’m doing for now in this post is to summarise the key points of the work, to make it more accessible to students, as it’s an excellent example of a New Right point of view on gender roles. At some point I’ll get round to adding in some of the responses and criticisms of Danmore’s work.

Google’s Ideological Echo Chamber – A Summary of the Main Points

(Full Text – Googles-Ideological-Echo-Chamber)

Danmore starts off the article by outlining (crudely) the difference between left and right ideologies, before suggesting that his list of possible biological causes of the gender gap (below) are ‘’non-biased”

 It’s also worth mentioning that Danmore does qualify a lot of what he says, stating more than once that he doesn’t deny that sexism exists, he also states that there is considerable ‘biological overlap’ between men and women, so there are plenty of women who are biologically predisposed (as he would put it) towards techy jobs and leadership.

I’ve cut out quite a lot of the text, so as to just include the main arguments and evidence (there’s not much evidence cited) – anything in normal text is word for word from the original, anything italicised are my additions.

 Possible non-bias causes of the gender gap in tech:

On average, men and women biologically differ in many ways. These differences aren’t just socially constructed because:

  • They’re universal across human cultures
  • They often have clear biological causes and links to prenatal testosterone
  • Biological males that were castrated at birth and raised as females often still identify and act like males
  • The underlying traits are highly heritable
  • They’re exactly what we would predict from an evolutionary psychology perspective

Note, I’m not saying that all men differ from all women in the following ways or that these differences are “just.” I’m simply stating that the distribution of preferences and abilities of men and women differ in part due to biological causes and that these differences may explain why we don’t see equal representation of women in tech and leadership.

Many of these differences are small and there’s significant overlap between men and women, so you can’t say anything about an individual given these population level distributions.

Danmore includes the following diagrams to make his point:

Googles Ideological Echo Chamber

Personality differences

Women, on average, have more (this heading is linked to a Wikipedia article on sex differences in psychology)

  • Openness directed towards feelings and aesthetics rather than ideas.
  • Women generally also have a stronger interest in people rather than things, relative to men (also interpreted as empathizing vs. systemizing).
  • These two differences in part explain why women relatively prefer jobs in social or artistic areas. More men may like coding because it requires systemizing.
  • Extraversion expressed as gregariousness rather than assertiveness. Also, higher agreeableness. This leads to women generally having a harder time negotiating salary, asking for raises, speaking up, and leading.
  • Neuroticism (higher anxiety, lower stress tolerance) – This may contribute to the lower number of women in high stress jobs.

In this section Danmore cites two journal articles (all other links are not academic so I haven’t included them) to back up his views:

Men’s higher drive for status

We always ask why we don’t see women in top leadership positions, but we never ask why we see so many men in these jobs.

These positions often require long, stressful hours that may not be worth it if you want a balanced and fulfilling life.

Status is the primary metric that men are judged on, pushing many men into these higher paying, less satisfying jobs for the status that they entail.

Note, the same forces that lead men into high pay/high stress jobs in tech and leadership cause men to take undesirable and dangerous jobs like coal mining, garbage collection, and firefighting, and suffer 93% of work-related deaths.

  • Danmore doesn’t cite any authoritative evidence to back up the views in this section. 

The rest of the document

There are four further sections in the document in which Danmore covers:

  • Non-discriminatory ways to reduce the gender gap – actually he makes some pretty sensible suggestions here IMO, such as making work more collaborative.
  • A section on the harm of Google’s biases
  • A section on ‘why we’re blind’ – i.e. why we’re blind to the apparent ‘objective truth’ of the fact that men are leaders because they’re less neurotic etc.
  • A final section of suggestions – in which he basically suggests that we should be more tolerant of conservative views and not discriminate in ‘authoritarian ways’.

 

 

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