We need to deal with so much information from all sorts of media these days, that reputation is becoming a larger and larger factor in our society.
In the past the path to publication was much harder, so something that was published acquired a reputation simply by virtue of the publication process. These days however, it's cheap and easy to publish. Fake news sites are ones that have the trappings of a real news site, but initially attract people by appealing to biases. They trade off the gain in reputation simply by appearing like a reputable site and having a plausable domain name.
We often rely on "reputation chains" to validate information. We believe a study because scientists have reviewed the study as part of the peer review process. The study has gained from the reputation of the journal, and to the more knowledgable - from the reputation of the reviewing scientists. Unfortunately sometimes people with good reputations can spread misinformation, so we still need to be critical as to the veracity of the information we receive. Our cognative biases can cause us to reject true information, so we need to be caution when rejecting information from a reputable source.
We also have more reputation transmission mechanisms these days. We have accreditations, charter groups, and social networking sites for signalling reputation. We have awards and prizes for boosting reputation. Reputation is an increasingly bankable attribute these days.
There is a great post over at Charlie Stross' Blog that gives the text of his keynote at the 34th Chaos Communication Congress in Leipzig, December 2017. He makes some interesting points about old, slow AI - i.e. corporations, and compares them to cannibalistic organisms that shed people like cells. He talks about the ways the standard limiter of regulation are failing (regulatory capture and regulatory lag). He ends with a fairly negative assessment of where we are heading. It's a thought-provoking talk, and well worth reading / watching.
Back in the late 80's/early 90's, I used to argue that programmers should do their coding on an 8086 machine, an IBM XT for example, rather than something more powerful like a 286. My argument was that by using a slow machine, you had the same user experience as your average user, and you could optimize the program appropriately.
Facebook has recently got into trouble over an accusation that they are suppressing conservative news stories in the trending news categories. Facebook have an algorithmic system that promotes trending topics to a human curation team, who make the final decision about what gets promoted. Obviously human beings have bias. One of the interesting things that has happened in finance is that banks are using algos more and more to ensure that humans aren't involved in situations where there can be a conflict of interest. One example is the 4pm FX fix which are now required to be handled algorithmically. There's a trend here - algorithms are being used to ensure fairness. Will media companies be forced to have algorithmic editors to remove bias from reporting?
I've been thinking a lot recently about the mistakes I make in predicting things. Often I will just observe a trend, and then extrapolate that trend into the future. This will be my prediction. The world doesn't work like that though. Trends will last for a while, but then something changes, and before you know it the world has changed direction.
I want to think more about how and why a current trend could change direction. For example - what would it take for the trend of rising property prices in London to change direction?
I've been reading the "Beyond Scarcity" series on FTAlphaville recently, and it's made some very interesting points. The posts argue that the current economic environment is deflationary with regard to goods. I think that is true, and one of the reasons is because of technology. Firstly technology is constantly making everything more efficient and because of global competition this is both reducing the production costs and making goods cheaper. Secondly technology is causing structural unemployment, which means less people have money to spend and there is less money flowing around the economy. Other factors causing deflation are the tight monetary conditions, the aging population, and potentially the effects of quantitative easing.
There is an interesting post over at pieria.co.uk called "The Financialisation of Labour". Frances Coppola compares the changing economic incentives between a company making a capital investment in a slave and an employee. She then suggests replacing the word "slave" with the word "robot".