Q: What do musicians do?
A: Create and share their art!
Q: How does a musician make money?
Hint: It’s all about the data.
The argument here is really about product flow vs. art. According to Spotify, the quality of artistic expression is not what’s important to listeners, it’s all about the product flow. An oversupply of crap is still, well, crap. Spotify needs data, not music. They want to use musicians to mine their data network value to justify their share price.
Streaming services as distribution networks are not friends to artists.
Seven out of the top 10 most valuable companies in the world are tech companies that either directly generate profit from data or are empowered by data from the core. Multiple surveys show that the vast majority of business decision makers regard data as an essential asset for success. We have all experienced how data is shifting this major paradigm shift for our personal, economic and political lives. Whoever owns the data owns the future.
But who’s producing the data? I assume everyone in this room has a smartphone, several social media accounts and has done a Google search or two in the past week. We are all producing the data.
The Information Age is different in many ways. This is why digital formats have roiled physical formats across all the creative industries. We need to think outside the box.
Interesting article from an academic expert (my annotations in red):
a digital platform is either large or dead.
Why economics must go digital
One of the biggest concerns about today’s tech giants is their market power. At least outside China, Google, Facebook, and Amazon dominate online search, social media, and online retail, respectively. And yet economists have largely failed to address these concerns in a coherent way. To help governments and regulators as they struggle to address this market concentration, we must make economics itself more relevant to the digital age.
Digital markets often become highly concentrated, with one dominant firm, because larger players enjoy significant returns to scale. For example, digital platforms incur large upfront development costs but benefit from low marginal costs once the software is written. They gain from network effects, whereby the more users a platform has, the more all users benefit. And data generation plays a self-reinforcing role: more data improves the service, which brings in more users, which generates more data. To put it bluntly, a digital platform is either large or dead.
As several recent reports (including one to which I contributed) have pointed out, the digital economy poses a problem for competition policy. Competition is vital for boosting productivity and long-term growth because it drives out inefficient producers and stimulates innovation. Yet how can this happen when there are such dominant players?
Today’s digital behemoths provide services that people want: one recent study estimated that consumers value online search alone at a level equivalent to about half of US median income. Economists, therefore, need to update their toolkit. Rather than assessing likely short-term trends in specific digital markets, they need to be able to estimate the potential long-term costs implied by the inability of a new rival with better technology or service to unseat the incumbent platform.
This is no easy task because there is no standard methodology for estimating uncertain, non-linear futures. Economists even disagree on how to measure static consumer valuations of free digital goods such as online search and social media. And although the idea that competition operates dynamically through firms entering and exiting the market dates back at least to Joseph Schumpeter, the standard approach is still to look at competition among similar companies producing similar goods at a point in time.
The characteristics of digital technology pose a fundamental challenge to the entire discipline. As I pointed out more than 20 years ago, the digital economy is “weightless.” Moreover, many digital goods are non-rival “public goods”: you can use software code without stopping others from doing so, whereas only one person can wear the same pair of shoes. And they require a substantial degree of trust to have any value: we need to experience them to know whether they work, and social influence is often crucial to their diffusion.
Yet standard economics generally assumes none of these things. Economists will bridle at this statement, rightly pointing to models that accommodate some features of the digital economy. But economists’ benchmark mental world – particularly their instinctive framework for thinking about public policy questions – is one where competition is static, preferences are fixed and individual, rival goods are the norm, and so on.
Starting from there leads inexorably to presuming the “free market” paradigm. As any applied economist knows, this paradigm is named for a mythical entity. But this knowledge somehow does not give rise to an alternative presumption, say, that governments should supply certain products.
This instinct may be changing. One straw in the wind is the call by Jim O’Neill, a former Goldman Sachs economist who now heads the Royal Institute of International Affairs (Chatham House), for public research and production of new antibiotics. Having led a review of the spread of anti-microbial resistance – which will kill millions of people if new drugs are not discovered – O’Neill is dismayed by the lack of progress made by private pharmaceutical companies.
Drug discovery is an information industry, and information is a non-rival public good which the private sector, not surprisingly, is under-supplying. [Yes – this is what intellectual property rights/copyrights/patents is all about. The problem is attributing the value created by the sharing of information. We may be able to solve that with blockchain ledgers.] That conclusion is not remotely outlandish in terms of economic analysis. And yet the idea of nationalizing part of the pharmaceutical industry is outlandish from the perspective of the prevailing economic-policy paradigm.
Or consider the issue of data, which has lately greatly exercised policymakers. Should data collection by digital firms be further regulated? Should individuals be paid for providing personal data? [Yes, they should. Personal data is as proprietary as personal labor and personal ideas. Making sure users get paid for their data changes the business models of these natural monopolies.] And if a sensor in smart-city environment records that I walk past it, is that my data, too? The standard economic framework of individual choices made independently of one another, with no externalities, and monetary exchange for the transfer of private property, offers no help in answering these questions. [Yes, because we don’t yet assign value to shared information. We rely on the property rights of tangible assets.]
Economic researchers are not blameless when it comes to inadequate policy decisions. We teach economics to people who go out into the world of policy and business, and our research shapes the broader intellectual climate. The onus now is on academics to establish a benchmark approach to the digital economy and to create a set of applied methods and tools that legislators, competition authorities, and other regulators can use.
Mainstream economics has largely failed to keep up with the rapid pace of digital transformation, and it is struggling to find practical ways to address the growing power of dominant tech companies. If the discipline wants to remain relevant, then it must rethink some of its basic assumptions.
As we can read from this article and Facebook’s internal management debates, Web 2.0 (of which the GAFA companies are the archetypes) is built on a data land grab. It’s rather similar to the actual land grab that the European powers battled over for the New World, then with the colonization of Africa and Asia.
Data is now a valuable resource that has been priced up there with land and capital. Naturally, the tech oligopolies and their startup wannabes all want to grab as much as possible. And who are they grabbing it from? The network users of course.
Web 3.0 is all about democratizing the value and monetization of personal networked data. It’s about decentralized ownership and control, much like the desire to own and control the fruits of one’s labor that ended slavery. Web 3.0 is the future, because Web 2.0 is unsustainable.
in 20 tweets…
Nice article on Medium:
I would add that the major problems for artists in the digital age stem from the explosion of new supply of content. This drives the price down and the search costs of discovery up. The failure then becomes that artists can’t find their audiences and consumers can’t find the content they desire. For poets this means finding an audience not necessarily to sell poetry; rather more important is to find readers and appreciators of their poetry.
Large centralized network servers based on algorithms can’t solve this problem without commoditizing content and delivering the most popular but mundane content churned out by those metrics.
We need to empower the human by connecting the creative.
This is a review of British historian Niall Ferguson’s new book titled The Square and the Tower: Networks, Hierarchies and the Struggle for Global Power. It’s interesting to take the long arc of history into account in this day and age of global communication networks, which might seem to herald the permanent dominance of networks over hierarchies. That history cautions us otherwise.
Ferguson notes two predominant ages of networks: the advent of the printing press in 1452 that led to an explosion of networks across the world until around 1800. This was the Enlightenment period that helped transform economics, politics, and social relations.
Today, the second age of networks consumes us, starting at about 1970 with microchip technology and continuing forward to the present. It is the age of telecommunications, digital technology, and global networks. Ours is an age where it seems “everything is connected.”
Ferguson notes that, beginning with the invention of written language, all that has happened is that new technologies have facilitated our innate, ancient urge to network – in other words, to connect. This seems to affirm Aristotle’s observation that “man is a social animal,” as well as a large library of psychological behavioral studies over the past century. He also notes that most networks may reflect a power law distribution and be scale-free. In other words, large networks grow larger and become more valuable as they do so. This means the rich get richer and most social networks are profoundly inegalitarian. This implies that the GoogleAmazonFacebookApple (GAFA) oligarchy may be taking over the world, leaving the rest of us as powerless as feudal serfs.
But there is a fatal weakness inherent to this futuristic scenario, in that complex networks create interdependent relationships that can lead to catastrophic cascades, such as the global financial crisis of 2008. Or an explosion of “fake news” and misinformation spewed out by global gossip networks.
We are also seeing a gradual deconstruction of networks that compete with the power of nation-state sovereignty. This is reflected in the rise of nationalistic politics in democracies and authoritarian monopoly control over information in autocracies.
However, from the angle of hierarchical control, Ferguson notes that failures of democratic governance through the administrative state “represents the last iteration of political hierarchy: a system that spews out rules, generates complexity, and undermines both prosperity and stability.”
These historical paths imply that the conflict between distributed networks and concentrated hierarchies is likely a natural tension in search of an uneasy equilibrium.
Ferguson notes “if Facebook initially satisfied the human need to gossip, it was Twitter – founded in March 2006 – that satisfied the more specific need to exchange news, often (though not always) political.” But when I read Twitter feeds I’m thinking Twitter may be more of a tool for disruption rather than constructive dialogue. In other words, we can use these networking technologies to tear things down, but not so much to build them back up again.
As a Twitter co-founder confesses:
‘I thought once everybody could speak freely and exchange information and ideas, the world is automatically going to be a better place,’ said Evan Williams, one of the co-founders of Twitter in May 2017. ‘I was wrong about that.’
Rather, as Ferguson asserts, “The lesson of history is that trusting in networks to run the world is a recipe for anarchy: at best, power ends up in the hands of the Illuminati, but more likely it ends up in the hands of the Jacobins.”
Ferguson is quite pessimistic about today’s dominance of networks, with one slim ray of hope. As he writes,
“…how can an urbanized, technologically advanced society avoid disaster when its social consequences are profoundly inegalitarian?
“To put the question more simply: can a networked world have order? As we have seen, some say that it can. In the light of historical experience, I very much doubt it.”
That slim ray of hope? Blockchain technology!
A thought-provoking book.