Science Technology Society

Besides lacking a desirable alternative, the final problem with destroying civilization as we know it is that the alternative, such as it has been imagined by the self-described “haters of civilization”, would not support but a fraction of the people alive today. In other words, the collapse of civilization would kill billions. Ironically the poorest rural inhabitants would fare the best, as they could retreat to hunting gathering with the least hurdle, but billions of urbanites would die once food ran out and disease took over. The anarcho-primitives are rather sanguine about this catastrophe, arguing that accelerating the collapse early might save lives in total.

The ultimate problem is that the paradise the Kaczynski is offering, the solution to civilization so to speak, is the tiny, smoky, dingy, smelly wooden prison cell that absolutely nobody else wants to dwell in. It is a paradise billions are fleeing from. Civilization has its problems but in almost every way it is better than the Unabomber’s shack. The Unabomber is right that technology is a holistic, self-perpetuating machine. He is wrong to bomb it for many reasons, not the least is that the machine of civilization offers us more actual freedoms than the alternative. There is a cost to run this machine, a cost we are only beginning to reckon with, but so far the gains from this ever enlarging technium outweigh the alternative of no machine at all.

The challenge of personal computing became manifest at an opportune time. The broad project of cognitive science, which incorporated cognitive psychology, artificial intelligence, linguistics, cognitive anthropology, and the philosophy of mind, had formed at the end of the 1970s. Part of the programme of cognitive science was to articulate systematic and scientifically-informed applications to be known as "cognitive engineering". Thus, at just the point when personal computing presented the practical need for HCI, cognitive science presented people, concepts, skills, and a vision for addressing such needs. HCI was one of the first examples of cognitive engineering. Other historically fortuitous developments contributed to establishment of HCI. Software engineering, mired in unmanageable software complexity in the 1970s, was starting to focus on nonfunctional requirements, including usability and maintainability, and on non-linear software development processes that relied heavily on testing. Computer graphics and information retrieval had emerged in the 1970s, and rapidly came to recognize that interactive systems were the key to progressing beyond early achievements. All these threads of development in computer science pointed to the same conclusion: The way forward for computing entailed understanding and better empowering users.

One of the most significant achievements of HCI is its evolving model of the integration of science and practice. Initially this model was articulated as a reciprocal relation between cognitive science and cognitive engineering. Later, it ambitiously incorporated a diverse science foundation, notably Activity Theory, distributed cognition, and ethnomethodology, and a culturally embedded conception of human activity, including the activities of design and technology development. Currently, the model is incorporating design practices and research across a broad spectrum. In these developments, HCI provides a blueprint for a mutual relation between science and practice that is unprecedented.

In the latter 1980s and early 1990s, HCI assimilated ideas from Activity Theory, distributed cognition, and ethnomethodology. This comprised a fundamental epistemological realignment. For example, the representational theory of mind, a cornerstone of cognitive science, is no longer axiomatic for HCI science. Information processing psychology and laboratory user studies, once the kernel of HCI research, became important, but niche areas. The most canonical theory-base in HCI now is socio-cultural, Activity Theory. Field studies became typical, and eventually dominant as an empirical paradigm. Collaborative interactions, that is, groups of people working together through and around computer systems (in contrast to the early 1980s user-at-PC situation) have become the default unit of analysis. It is remarkable that such fundamental realignments were so easily assimilated by the HCI community.