The New Ecology 21
will feed into many of the discussions of relations between technologies,
users, and organisations throughout this book, it is tempting to coin
a phrase to better describe those relations: technological stochastism.
Rather than attempting to define causal relations within different paradigms, a media ecology based on stochastic procedures would outline
the probabilities of particular patterns of behaviour emerging within
certain conditions.
Technology companies – the great disruptors of Silicon Valley and
elsewhere – have greatly transformed the media landscape of the early
twenty-first century. Of that, there can be no doubt: and yet the effects
of their innovations are by no means the result of a simple “billiard
ball” view of technological and media determinism. As we shall see in
subsequent chapters, companies such as Google and Facebook have often struggled to deal with the unintended effects of forces which they
have set in motion. What is clear, however, is that the increasing automation of cognitive activities through algorithms powered by increasingly sophisticated computers – what is usually referred to as artificial
intelligence – will bring about even more profound changes.
The Ghost in the Machine
In his book Life 3.0: Being Human in the Age of Artificial Intelligence,
Max Tegmark offers a hypothetical scenario in which an “Omega
Team” of researchers produces an artificial intelligence, “Prometheus”,
that rapidly approaches what some of those working in the field of AI
refer to as a “singularity” – that moment when such an intelligence surpasses human capabilities:
Within a year of the first launch, they had added remarkably good
news channels to their lineup all over the globe. As opposed to their
other channels, these were deliberately designed to lose money, and
were pitched as a public service. In fact, their news channels generated no income whatsoever: they carried no ads and were viewable
free of charge by anyone with an internet connection. The rest of the
media empire was such a cash-generating machine that they could
spend far more resources on their news service than any other journalistic effort had done in world history – and it showed. Through
aggressive recruitment with highly competitive salaries of journalists and investigative reporters, they brought remarkable talent and
findings to the screen. Through a global web service that paid anybody who revealed something newsworthy, from local corruption to
a heartwarming event, they were usually the first to break a story.
At least that’s what people believed: in fact, they were often first
because stories attributed to citizen journalists had been discovered
by Prometheus via real-time monitoring of the internet.
47
will feed into many of the discussions of relations between technologies,
users, and organisations throughout this book, it is tempting to coin
a phrase to better describe those relations: technological stochastism.
Rather than attempting to define causal relations within different paradigms, a media ecology based on stochastic procedures would outline
the probabilities of particular patterns of behaviour emerging within
certain conditions.
Technology companies – the great disruptors of Silicon Valley and
elsewhere – have greatly transformed the media landscape of the early
twenty-first century. Of that, there can be no doubt: and yet the effects
of their innovations are by no means the result of a simple “billiard
ball” view of technological and media determinism. As we shall see in
subsequent chapters, companies such as Google and Facebook have often struggled to deal with the unintended effects of forces which they
have set in motion. What is clear, however, is that the increasing automation of cognitive activities through algorithms powered by increasingly sophisticated computers – what is usually referred to as artificial
intelligence – will bring about even more profound changes.
The Ghost in the Machine
In his book Life 3.0: Being Human in the Age of Artificial Intelligence,
Max Tegmark offers a hypothetical scenario in which an “Omega
Team” of researchers produces an artificial intelligence, “Prometheus”,
that rapidly approaches what some of those working in the field of AI
refer to as a “singularity” – that moment when such an intelligence surpasses human capabilities:
Within a year of the first launch, they had added remarkably good
news channels to their lineup all over the globe. As opposed to their
other channels, these were deliberately designed to lose money, and
were pitched as a public service. In fact, their news channels generated no income whatsoever: they carried no ads and were viewable
free of charge by anyone with an internet connection. The rest of the
media empire was such a cash-generating machine that they could
spend far more resources on their news service than any other journalistic effort had done in world history – and it showed. Through
aggressive recruitment with highly competitive salaries of journalists and investigative reporters, they brought remarkable talent and
findings to the screen. Through a global web service that paid anybody who revealed something newsworthy, from local corruption to
a heartwarming event, they were usually the first to break a story.
At least that’s what people believed: in fact, they were often first
because stories attributed to citizen journalists had been discovered
by Prometheus via real-time monitoring of the internet.
47