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This paper presents the outcome of a study conducted at the Royal Devon and Exeter Hospital in which a prediction market was established in order to forecast demand for services. To the researcher's knowledge, it does not appear that prediction markets have been previously utilized in a healthcare environment.

Google Search itself provides one of the most familiar examples of predictive intelligence. When you enter keywords in the search box, Google predicts what you are interested in and then presents you with results that match that intent. Since it released the first version of its Prediction API in 2010, Google has made some of these methods available to developers. Adoption among developers has not been high because machine learning requires a lot of infrastructure and validation to produce accurate results. Developers have also reported discomfort with basing products on black box APIs.

"It is somewhat safe to predict that AI will continue to be at the top of the hype cycle in 2018. But the following 51 predictions also envision it becoming more practical and useful, automating some jobs and augmenting many others, combining machine learning and big data for fresh insights, with chatbots proliferating in the enterprise."

These scenarios describe two predictions in what will be an algorithmic and smart machine driven world where people and machines must define harmonious relationships.

Predictive analytics uses many techniques from data mining, statistics, machine learning and AI.

"'Knowledge creation trumps knowledge transfer' 'Diversity trumps ability' 'Diversity across firms trumps diversity within companies' These are some of the themes explored in this interesting article from Business Week Magazine. The Las Vegas casino Hurrahs is tapping into the power of prediction markets specifically to innovate. The importance of particular kinds of diversity are also explored. If you want to know more about Prediction Markets, we are building a considerable KIN resource on this here and the KIN Quarterly Workshop on 2nd December will cover this topic. Thanks go to Jenny Ambrozek for pointing out this fascinating article. "

Michigan State University has over 450,000 alumni around the world. The school's University Advancement department sought to create a representation of alumni and donor sentiment and likelihood of philanthropic engagement based on data gathered from social media. However, these analyses often took weeks to process, limiting the school's ability to gather valuable insights in a timely manner. This case study describes how MSU leveraged business intelligence and predictive analytics to gain deep insight into an individual alum's potential to give, resulting in the following positive results: -An annual ROI of 55% -An average annual benefit of $34,434 -And more The case study purports to show how organisations can identify new opportunities for revenue generation by embracing a BI and predictive analytics strategy.

Predictive analytics for sales and marketing. Transforming big data into customer knowledge

Prediction Markets Google Group. The Group comes compleat with some very opinionated characters. Can be useful to watch the ambient flow from a distance for nuggets like the Economist article. Suggest people subscribe with a non-work id that they can check at their leisure so any posts don't clutter work email on handhelds.

The company as a wiki. US Company Best Buy embraces WEB 2.0 including prediction markets. Best Buy's CEO talking about prediction markets at zeitgeist '08 (starting at 9:50)

This is my comment about this

Harrah's, the casino entertainment company, is beginning to explore how to create commercially useful knowledge by applying a much-hyped knowledge management tool-prediction markets-in a very new contex

" 'Knowledge creation trumps knowledge transfer' 'Diversity trumps ability' 'Diversity across firms trumps diversity within companies' These are some of the themes explored in this interesting article on how the Las Vegas casino Hurrahs is tapping into the power of prediction markets specifically to innovate. Thanks to Jenny Ambrozek for pointing this article out."

Online prediction marketplace. KIN is experimenting with this in advance of our Winter Quarterly workshop

Employee Participation in the Flow: Prediction Markets, Part 1

An interesting way of starting research on a topic. Example using "Prediction Market"

Though US-centric, this Pew Report "Public Predictions for the Future of Workforce Automation" gives some insight to workforce attitudes to automation. Despite their expectations that technology will encroach on human employment in general, most workers think that their own jobs or professions will still exist in 50 years. Heads in the sand, or justifiable pessimism?

Experts predict a 50 percent chance that AI will be better than humans at more or less everything in about 45 years time, i.e. the point of 'Singularity'.

Last year was huge for advancements in artificial intelligence and machine learning. But 2017 may well deliver even more. Here are five key things to look forward to.

Humans are biased, and the biases we encode into machines are then scaled and automated. This is not inherently bad (or good), but it raises the question: how do we operate in a world increasingly consumed with "personal analytics" that can predict race, religion, gender, age, sexual orientation, health status and much more.

Crowd Clarity is a new entrant to the field of Prediction markets for firms.