In The Making of Donald Trump, David Johnston identifies the tactics used by Trump to deflect inquiries into his many shady dealings and questionable decisions. Sometimes this is a matter of outright threats, with an enthusiasm for litigation (1,900 suits as plaintiffs) coupled with an explicitly articulated philosophy of vengeance proving a dangerous combination for any who dare to cross him. But somewhat contrary to his public image as a blundering fool, he is often much more subtle than this, engaging in strategies of deflection and misdirection with all the deftness of the most accomplished public relations manager. In other cases, it just becomes weird, with Trump willing to publicly deny that a recording he had previously admitted to be of his own voice was anything other than a hoax:
This combination of viciousness, skilfulness and brazenness has left him insulated from meaningful scrutiny. But what has he averted in this way? What might have happened but hasn’t? On page 154 Johnston offers a description which has caught my imagination:
Together, these strategies – muddying the facts and deflecting inquiries into past conduct – help ensure that Trump’s carefully crafted public persona will not be unmade. He will not suffer the curtain to be pulled back to reveal a man who tricked society into thinking he was all wise and all powerful.
This public persona which has been crafted, sometimes deliberately while at other times impulsively, remains intact. I’m interested in what such a ‘pulling back of the curtain’ requires to be effective: the sustained attention of an audience, a sufficient familiarity with the person(a) in question, a prolonged campaign to sort fact from fiction and a lack of contestation concerning this process of sorting.
What is being framed somewhat unhelpfully as a ‘post-truth era’ are the conditions under which this ceases to be possible. There’s lots of ways in which we could try and explain them, not all of which are necessarily mutually exclusive. The collapse of authority in late modernity. The acceleration of communication. The weakening of journalism and the dominance of public relations. Theories of social change should be able to account for the specifics of such cases, rather than simply allowing them to be rendered thematically.
In his InfoGlut, Mark Andrejevic takes issue with the assumption that fostering ‘disbelief’ or ‘challenge’ is necessarily subversive. As he puts it, “strategies of debunkery and information proliferation can work to reinforce, rather than threaten, relations of power and control” (loc 293). Recognising this in the abstract is important but I intend to read more about the specific cases in which these tactics are used regressively, as I’m increasingly fascinated by the extent to which these tactics are informed (or not) by epistemological and ontological understandings (even if these words are not used).
Under these conditions, what Andrejevic describes as the ‘big data divide’ seems ever more prescient by the day. From loc 464:
The dystopian version of information glut anticipates a world in which control over the tremendous amount of information generated by interactive devices is concentrated in the hands of the few who use it to sort, manage, and manipulate. Those without access to the database are left with the “poor person’s” strategies for cutting through the clutter: gut instinct, affective response, and “thin- slicing” (making a snap decision based on a tiny fraction of the evidence). The asymmetric strategies for using data highlight an all- too- often overlooked truth of the digital era: infrastructure matters. Behind the airy rhetoric of “the cloud,” the factories of the big data era are sprouting up across the landscape: huge server farms that consume as much energy as a small city. Here is where data is put to work – generating correlations and patterns, shaping decisions and sorting people into categories for marketers, employers, intelligence agencies, healthcare providers, financial institutions, the police, and so on. Herein resides an important dimension of the knowledge asymmetry of the big data era – the divide between those who generate the data and those who put it to use by turning it back upon the population. This divide is, at least in part, an infrastructural one shaped by ownership and control of the material resources for data storage and mining. But it is also an epistemological one –a difference in the forms of practical knowledge available to those with access to the database, in the way they think about and use information.