Toward human-centered algorithm design

Abstract

As algorithms pervade numerous facets of daily life, they are incorporated into systems for increasingly diverse purposes. These systems' results are often interpreted differently by the designers who created them than by the lay persons who interact with them. This paper offers a proposal for human-centered algorithm design, which incorporates human and social interpretations into the design process for algorithmically based systems. It articulates three specific strategies for doing so: theoretical, participatory, and speculative. Drawing on the author's work designing and deploying multiple related systems, the paper provides a detailed example of using a theoretical approach. It also discusses findings pertinent to participatory and speculative design approaches. The paper addresses both strengths and challenges for each strategy in helping to center the process of designing algorithmically based systems around humans.

Innovating Metrics for Smarter, Responsive Cities

“…This work explores the challenges posed by big (and small) data in relation to smart cities and the opportunities and implications for urban metrics. In response to the need for theory [31] and methodologies for innovating metrics for data in smart cities in relation to algorithms and synthetic indicators [1], [20] in support of meaningfulness [5], [80], the involvement of people [80], and the unmeasurable [77], this work advances a framework for innovating metrics for smarter people in smart, responsive cities. Several contributions emerge from this work in that an innovation framework for emergent and evolving ambient metrics is developed and operationalized; an early stage adaptation of Anderson's body insight scale (BIS) for application in relation to metrics in smart city environments for tension, comfort, and safety is explored along with acceptable confidence interval based estimations of reliability for the scale and the use of Cronbach's Alpha to measure internal consistency and scale reliability for items; and a series of variables for awareness, learning, openness, and engagement are surfaced for consideration in the innovating and extending of urban metrics.…”

“…Data as improvisatory is articulated by Pink et al [30] in terms of the creativity associated with "human activity" around interpretations of broken data. Data as meaningful is addressed by Thakuriah et al [20] and Joss [46] as well as Baumer [80] in terms of evolving traditional algorithm design for greater involvement of people on the one hand and on the other hand by Bell et al [5] focusing on metrics and co-design for smart cities. The performative nature of data is addressed by Zook [23] in terms of inputs and outputs for "anticipatory governance" and by Parmiggiani, Monteiro, and Østerlie [55] in relation to remote, inaccessible situations as synthetic, while performance aspects are addressed by Caird et al [63] and Bosch et al [65].…”

“…However, Zook [23] cautions that while "big" data may seem to be "better" producing accessible metrics and visualizations, this may contribute to "realities that mischaracterize and constrain". For example, Baumer [80] proposes a human-centered algorithm design (HCAD) in response to gaps or disconnects between algorithm metrics focused on performance on the one hand and the need for incorporating "human and social interpretations" on the other. Baumer [80] identifies three approaches to making algorithmic design more people-centered, focusing on the theoretical, speculative, and participatory.…”

“…For example, Baumer [80] proposes a human-centered algorithm design (HCAD) in response to gaps or disconnects between algorithm metrics focused on performance on the one hand and the need for incorporating "human and social interpretations" on the other. Baumer [80] identifies three approaches to making algorithmic design more people-centered, focusing on the theoretical, speculative, and participatory. According to Baumer [80] "meaning making" points to "limitations of traditional algorithm design and evaluation methods" and as such, "algorithmic support for the processes of meaning making is where human-centered approaches stand to contribute the most".…”

“…Baumer [80] identifies three approaches to making algorithmic design more people-centered, focusing on the theoretical, speculative, and participatory. According to Baumer [80] "meaning making" points to "limitations of traditional algorithm design and evaluation methods" and as such, "algorithmic support for the processes of meaning making is where human-centered approaches stand to contribute the most". Coletta and Kitchin [81] give "attention to how the temporality of cities is being reshaped by systems and infrastructure that capture, process and act on real-time data" so as to "map out the ways in which city-scale Internet of Things infrastructures, and their associated networks of sensors, meters, transponders, actuators and algorithms, are used to measure, monitor and regulate the polymorphic temporal rhythms of urban life".…”