Have bookmarked but not read Bruce Sterling’s thoughts on future of money yet. Still trying to make sense of artificial intelligence and what happens at micro and macro levels – this post will start to look at networks and markets.
Technologies are communicating with other technologies across a network & there are many aspects at each layer, so does artificial intelligence offer anything better? Slightly off-topic of this post but investment in artificial intelligence itself could currently be seen as fairly high risk, if we do invest in these technologies and research, how will that make the world a better place now?
Also the communication of humans across these networks – social networks. Does decision making, consideration of ethics take place across networks (i.e. what makes up artificially intelligent software and hardware). Can a group decision or could it be a network decision be better than one made by an individual in relation to investment? Is that ethical in itself? This interesting 3 part interview from TransAlchemy raises a lot of questions relating to artificial intelligence and nanotechnology
Part 2 is 10 min approx, Part 3 is 8 min approx.
Investment decisions will also involve ethical considerations at a micro-level – the decisions made by one or few humans.
Quick economics & technology recap…
We choose to invest in products and services which are being traded and as we interact with more humans we encounter more choices. The organizations which produce these products and services generate revenues, have costs and some make profits. Some organizations have chosen to allow others to own part of their companies by investing in stocks, contracts and many other options. How do we keep track of all the different companies, how well they are performing – if they have chosen to issue shares, we can follow share prices. All the materials and resources which need to be mined, created, adapted and purchased in order to make the products and services can also have variations in prices which we can follow through indexes. There are also multiple types of insurance and contracts which provide alternative options for an investor who is unsure about a potential investment.
All these different types of things can be traded in markets which we can also follow. This results in a huge amount of data to be analysed which is not possible at a micro level without technology and super-processing. Throughout the 20th and 21st centuries, we have attempted to use technologies to help us understand better about what is going on (and as in all human societies we have a variety of different motives for doing so and make different ethical decisions). Models have been used (before computers and also using computers) to help try and understand why different organizations and groups of organizations perform differently. There has been a lot of research sponsored by the financial services industry in both technology and models research to try and exploit the markets to find better ways of analysing and managing risk and ultimately achieving better returns for investors. So physical computing networks have been used and now increasingly more social communication networks – I’ve seen at least three different stock applications / services available via Twitter appear in the last year.
Is there autonomy in markets?
Are markets open, self-governing (not talking about the role of government in regulating organisations, just as a principle), efficient – adjusting for random fluctuations / behaviour. Some of the earliest economic writing such as Adam Smith’s Wealth of Nations raises concepts of openness and free trading, 1 Investment decisions are made based on information that is available at a moment in time, the use of technologies has meant that even though technologies are capable of computing complex calculations, algorithms they do not necessarily provide data that is capable of being understood – i.e. financial and economic visualization is complex ! So technologies might not be able to provide openness and free trading as entities themselves.
Efficient Markets Hypothesis was developed by Eugene Fama, initially under supervision of Benoit Mandelbrot which looks at whether markets can provide a fair price, regardless of any complexity and information available:
“A financial market is fair game in which buyer balances seller. Given that the price at any particular moment must be the ‘right’ one…Multiply this thinking by the millions of daily deals of a bustling market and you conclude that the general market price must be ‘right’ as well – that is, that the published price reflects the market’s overall best guess…of what a stock is likely to profit its owner”2
Are the dynamics involved in markets and networks the same ? Tom Haskins defines them as different:
“COMPLICATED situations breed a MARKET order where GOOD practices handle the challenges. Rival firms position themselves with varied product/service mixes. Customers are constantly changing their needs, desires, preferences and perceptions. Technology, regulatory legislation and media coverage alters the commercial landscape. The complications defy categorization or the application of best practices. A big investment needs to be made in analyzing what is sensed about this panorama of complications prior to responding with good practices (Sense – Analyze – Respond). Market dynamics handle these challenges the best.
COMPLEX situations breed a NETWORK order where EMERGENT practices handle the challenges. Feedback loops, vicious & virtuous cycles, self-referential messages, layered problems, and self-organizing dynamics all defeat the deliberate formulation of practices. Too many facets have taken on a life of their own with highly interdependent, evolving dimensions. It’s better to let effective practices arise from immersion in the complexity. Probing the immediate situation without prior conditioning, preconceptions or assumptions will yield a clear sense of how to respond in the moment (Probe – Sense – Respond). Network dynamics handle these challenges the best.”3
Will leave it here for today, want to go and think some more about it.
2. Mandelbrot B, Hudson R, (2004) p55, The (Mis)behaviour of Markets, A Fractal View of Risk, Ruin and Reward, New Edition, Profile Books
3. Haskins T, (2009), Cynefin practices applied to TIMN, Growing Changing Learning Creating, available at: http://growchangelearn.blogspot.com/2009/05/cynefin-practices-applied-to-timn.html