Prediction markets as meta-episteme: Artificial intelligence, forecasting tournaments, prediction markets, and economic growth

被引:0
|
作者
Murphy, Ryan H. [1 ,2 ]
机构
[1] Bridwell Inst Econ Freedom, SMU Cox Sch Business, Dallas, TX USA
[2] Bridwell Inst Econ Freedom, SMU Cox Sch Business, POB 750333, Dallas, TX 75275 USA
关键词
D O I
10.1111/ajes.12546
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper presents a speculative framework suggesting that prediction markets (or its epistemic cousins such as artificial intelligence or forecasting tournaments) may constitute a break in the expansion of human knowledge in a manner similar to the impact of the Scientific and Industrial Revolutions. Just as the scientific understanding of the natural world facilitated the development of useful technologies to move far faster than what is allowed by blind evolution and tinkering, tools such as prediction markets allow for scientific knowledge to move faster than its current evolutionary process. The intellectual bases for these tools, such as the interpretation of probabilities as bets, are relatively recent additions to human knowledge, which may have significant implications for how we evaluate past thinkers, versus what is now possible or may be possible in the future.
引用
收藏
页码:383 / 392
页数:10
相关论文
共 50 条
  • [21] Artificial Intelligence-Based Model For Drought Prediction and Forecasting
    Kaur, Amandeep
    Sood, Sandeep K.
    [J]. COMPUTER JOURNAL, 2020, 63 (11): : 1704 - 1712
  • [22] Keeping a weather eye on prediction markets: The influence of environmental conditions on forecasting accuracy
    Sperb, Luis Felipe Costa
    Sung, Ming-Chien
    Johnson, Johnnie E. V.
    Ma, Tiejun
    [J]. INTERNATIONAL JOURNAL OF FORECASTING, 2019, 35 (01) : 321 - 335
  • [23] Sports Forecasting: A Comparison of the Forecast Accuracy of Prediction Markets, Betting Odds and Tipsters
    Spann, Martin
    Skiera, Bernd
    [J]. JOURNAL OF FORECASTING, 2009, 28 (01) : 55 - 72
  • [24] Mixed price and load forecasting of electricity markets by a new iterative prediction method
    Amjady, Nima
    Daraeepour, Ali
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2009, 79 (09) : 1329 - 1336
  • [25] Forecasting Foreign Exchange Markets Using Google Trends: Prediction Performance of Competing Models
    Wilcoxson, Jordan
    Follett, Lendie
    Severe, Sean
    [J]. JOURNAL OF BEHAVIORAL FINANCE, 2020, 21 (04) : 412 - 422
  • [26] A new prediction strategy for price spike forecasting of day-ahead electricity markets
    Amjady, Nima
    Keynia, Farshid
    [J]. APPLIED SOFT COMPUTING, 2011, 11 (06) : 4246 - 4256
  • [27] Designing a Crowd Forecasting Tool to Combine Prediction Markets and Real-Time Delphi
    Kloker, Simon
    Straub, Tim
    Weinhardt, Christof
    [J]. DESIGNING THE DIGITAL TRANSFORMATION, DESRIST 2017, 2017, 10243 : 468 - 473
  • [28] Artificial intelligence based prediction models: sales forecasting application in automotive aftermarket
    Turkbayragi, Mert Girayhan
    Dogu, Elif
    Albayrak, Y. Esra
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2022, 42 (01) : 213 - 225
  • [29] Prediction Models in Aneurysmal Subarachnoid Hemorrhage: Forecasting Clinical Outcome With Artificial Intelligence
    de Jong, Guido
    Aquarius, Rene
    Sanaan, Barof
    Bartels, Ronald H. M. A.
    Grotenhuis, J. Andre
    Henssen, Dylan J. H. A.
    Boogaarts, Hieronymus D.
    [J]. NEUROSURGERY, 2021, 88 (05) : E427 - E434
  • [30] Machine learning augmentation reduces prediction error in collective forecasting: development and validation across prediction markets with application to COVID events
    Gruen, Alexander
    Mattingly, Karl R.
    Morwitch, Ellen
    Bossaerts, Frederik
    Clifford, Manning
    Nash, Chad
    Ioannidis, John P. A.
    Ponsonby, Anne -Louise
    [J]. EBIOMEDICINE, 2023, 96