Rehg, William, McBurney, Peter, and Parsons, Simon. (2005). “Computer Decision-Support Systems for Public Argumentation: Assessing Deliberative Legitimacy,” AI & Society (19), 203-229.

  1. “decision-support systems for public policy argumentation” so far focus more on reasoning, and inference — the dialectic process — than rely on knowledge database; thus “argumentation systems” rather than “knowledge systems”
  2. CAH hits the bullseye: “If appropriately designed, such systems should be able to assist debate by tracking various claims and arguments, by searching databases for relevant information, and by continually updating and assessing the overall state of the debate.” (204)
  3. gaps between formal design and practice show that AI researchers need to “engage in interdisciplinary experimentation;” hang with the poliSci, Soc, and other social scientists; and participate in the public discourse system themselves (205)
  4. Zeno system
    1. EC-funded, GMD urban planning
    2. developers (Gordon and Karacapilidis) call it “mediation system”
    3. formalized IBIS (issue-based information system) model (Rittel & Webber 1973)
      1. issue: topic (“Where should we put the airport?”)
      2. position: some relevant statement (“We should put it in Bob’s cornfield.”)
      3. argument: statements for or against positions (“Bob’s cornfield is too close to the hospital.”)
    4. actually labels positions as acceptable or not based on established constraints
    5. supports real-time debates
    6. intuitive, graphical interfaces
  5. Risk Agora (McBurney and Parsons)
    1. Proposed for scientific debate “over the potential health and environmental risks of new chemicals and substances and the appropriate regulation of these substances” (207)
    2. like Zeno, labels arguments, seeks to give snapshot of overall status of debate
    3. not meant for real-time
    4. no intuitive, graphical interfaces
  6. Three key roles for argumentation systems:
    1. support participants (help citizens, mediators, decision-makers find info)
    2. serve orrery role (keep records)
    3. provide forum for dialogue
    4. systems not close to being participants or decision-makers
  7. Problem with evaluation of SDSS: how do we know it’s producing any better decisions than the old way? How do we measure the effectiveness of the old decision-making process? “The precise problem that interests us here, however, is the lack of an inherent, or independently accessible, standard of truth or correctness for urban planning decisions” (212) or any social decision, for that matter. Closely tied to our political biases!
    1. Think of it this way: plug in the CLDS, let it run for five years. How can I tell if Russ is making better decisions now than he was pre-CLDS?
  8. Standards from Schmidt-Belz et al. (1998)
    1. efficiency
    2. transparency
    3. non-coerciveness
    4. equality of participation
  9. Legitimacy: Four dimensions of “reasonable deliberative transformation”
    1. “self-transformation”
      1. deliberation central, not bargaining (the latter is the “conventional pluralist model”)
      2. delib focuses more moving people from self-interest to conception of common good; bargaining about maximizing util.
      3. participants willing to share info, learn from each other, even change (transform!) position (negotiators usu. hold some info back)
    2. substantive dialectical quality
      1. “truth” a bad measure!
      2. address all relevant information
      3. arrive at msot justifiable/reasonable outcome
      4. combination of expertise and values
    3. inclusiveness
    4. non-coerciveness
      1. not enough to give everyone access; you also have to make sure there’s not some aspect of the system that limits some users ability to have their say and to learn from other participants
      2. watch those mediators!
  10. formal procedures can be coercive, inhibit knowledge flow! Check with these three questions, based on the above roles:
    1. “Do the participant-support mechanisms favor some parties over others?”
    2. “Is the tracking or record keeping genuinely neutral — that is, can each stakeholder perceive that the system has represented his or her or its position, interests, calues, and arguments accurately?”
    3. “And does the forum structure (e.g., the sequencing of links at the user-interface) give some participants greater opportunity to influence the deliberation?” (222)
  11. Note that determine whether there is coercion, the researcher must become a participant, talk to the other participants, understand things from their context

McBurney, Peter, and Parsons, Simon. (2001). Intelligent systems to support deliberative democracy in environmental regulation. Information & Communications Technology Law, 10(1), 79-89.

Ugh! Abstract only, no full text! Get it!

Among normative models for democracy, the Deliberative Model suggests that public policy decisions should be made only following rational, public deliberation of alternative courses of action. This article argues that such a model is particularly appropriate for the assessment of environmental and health risks of new substances and technologies, and for the development of appropriate regulatory responses. To give operational effect to these ideas, a dialectical argumentation formalism for an intelligent system within which deliberative debates about risk and regulation can be conducted is proposed. The formalism draws on various philosophies of argumentation, scientific and moral discourse, and communicative action, due to Toulmin, Pera, Alexy and Habermas. (!!!)