Ahoona

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Ahoona [1] [2] is a free online social network that is focused on crowd-sourcing six elements of decision quality [3] to help people make better decisions in their daily lives. The project started through a National Science Foundation initiative known as I-Corps. [4] It has resulted in numerous media publications, [5] [6] TEDx talks, [7] TV coverage, [8] and distribution lists of professional decision making societies. [9] This web-based decision making project first crowd-sources the inputs to a decision and then makes a decision recommendation. The crowd-sourced elements include the bigger picture, the alternatives, the preferences, the uncertainties, the information and the pros and cons. A decision recommendation is made after the elements of decision quality are crowd-sourced using decision tree analysis, pros cons analysis or weight and rate analysis.

Contents

Motivation

While the field of decision analysis has advanced significantly in the last few decades, it has not penetrated the daily lives of the general public for use with their decisions. Contributing factors to this include :

The main purpose of the Ahoona project is to simplify the decision making process for individuals by crowdsourcing the elements of the decision and building a step-by-step decision analysis using the crowd-sourced elements.

History

The Ahoona project started in 2011 with an initiative from the National Science Foundation to operationalize research conducted at universities. The projected was found by Ali Abbas, then a professor at the University of Illinois at Urbana-Champaign together with graduate students and friends from Facebook.

Operation

Radar chart evaluating along the six elements of decision quality Six Elements of Decision Quality.png
Radar chart evaluating along the six elements of decision quality

Ahoona requires users to register with their real names. Once logged in a user may post a decision he is facing to the world or to a select group of friends or to himself. Instead of receiving arbitrary recommendations, responders to the decision post, are provided with categories (buckets) for which they provide responses. These categories comprise six elements of decision quality:

  1. the bigger picture,
  2. the alternatives,
  3. the preferences,
  4. the uncertainties,
  5. the information and
  6. the pros and cons.

Once the inputs are received a decision tree analysis tool uses the inputs; builds a step-by-step decision tree and makes a decision recommendation.

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References

  1. "Archived copy" (PDF). Archived from the original (PDF) on 2015-05-26. Retrieved 2015-07-30.{{cite web}}: CS1 maint: archived copy as title (link)
  2. "Teaching decision-making with social networks". illinois.edu.
  3. Howard, R. A and A. E. Abbas. 2015. Foundations of Decision Analysis. Pearson
  4. "Helping People Through the Decision-Making Process Using a Web-Based Application - NSF - National Science Foundation". nsf.gov.
  5. "UI prof's website tackles decision-making". news-gazette.com.
  6. INFORMS. "Helping Teens Make Life-Changing Decisions". informs.org. Archived from the original on 2015-09-12. Retrieved 2015-08-02.
  7. Decision making and the pursuit of "happy"-ness: Ali Abbas at TEDxUIUC. YouTube. 18 April 2014.
  8. "Calculating Good Life Choices". Chicago Tonight - WTTW.
  9. "[Jdm-society] AHOONA - A new social network for decision making". sjdm.org.
  10. Samuel D. Bond (1 September 2010). "Improving the Generation of Decision Objectives". ResearchGate.