Wednesday, April 27, 2016

The Power of Twitter

Let's suppose I want to find an intelligent review of a film.

If I just put the name of the film into Google, I will get endless repetitions of the synopsis, together with details of cinemas showing the film, or places to buy/download.

In my post You don't have to be smart to search here ... but it helps (Nov 2008), I outlined one possible trick. If you put the name of the film together with a random cultural icon (my example was Lacan), you will get reviews of the film that name-drop the icon. That immediately filters out all the standard cinema listings. However, you might need to try a number of different cultural icons until you strike lucky.

A second option is to subscribe to good magazines. When I watched the film Anomalisa, I didn't immediately make the connection with Schopenhauer. The connection was made for me by a fascinating review by Zadie Smith in the New York Review of Books.



Once you know that such a connection exists, you can use Google to find it. But Google won't make that connection for you - unless sufficient numbers of other people have already made that connection.

So here's a third option. Twitter allows you to have a list of intelligent film critics, and intelligent magazines containing intelligent film reviews. Either you decide for yourself what counts as intelligent, or you adopt someone else's list. Then you can search through the list for seriously intelligent reviews of the latest film. You can't do anything quite like this with Google.


When you search for something, Google can give you page after page of practically identical material - for example, hundreds of newspapers all repeating the same press release. What one really wants is a search engine that works out which page represents the original source, which pages represent replications with no added content or value, and which pages offer additional commentary and interpretation. It is possible that Twitter, with its conversational structure, may be closer to providing this kind of navigation. But only if the platform can achieve reasonable commercial viability without being polluted.

The Force of Goole

When people talk about Internet Binging, they aren't talking about using the world's fourth most popular internet search engine. According to @ruskin147's BBC Radio Four documentary The Force of Google this evening, people don't even use the generic phrase "searching the internet". They use the word "Google". I think I heard someone say that the word is now more popular than the word "eggs".

Rory discussed several ways that hard-boiled Google poaches Internet business, while scrambling our brains.

1.  Business is dependent on the caprice of Google ranking. Rory talks to the owner of a fly fishing company, which gets a significant proportion of his business via Google. When Google changed its algorithm in 2013, his webpage dropped from page one to page seven - almost equivalent to a commercial death penalty. Then inexplicably it climbed back again - the death penalty reprieved. Readers with long memories will remember the story of BMW (Feb 2006), which was banished from Google for three days in 2006.
 
2. In trying to be as helpful as possible to searchers, Google sometimes fails to respect the interests of other information providers. For example, if you search for hotels in Bury, you get Google's automatically curated list before you get lists from rival platforms such as TripAdvisor and Yelp. 

3. In the past, there has been some evidence that Google is biased towards controversial new technologies, perhaps because the technology vendors spend more on advertising than the technology sceptics. I have noted this apparent bias in relation to Biometrics (Nov 2003) and RFID (Nov 2005). Google now seems to have made some progress on this issue - Rory looked up "fracking" and got a more even-handed view from Google than from Bing.

4. Even without any obvious commercial or political agenda on Google's part, it is easy to see how Google's results could appear to show a lack of balance. Note for example the recent controversy about Unprofessional Hair. There have also been suggestions that Google page ranking could influence the public perception of politicians and thus sway elections.

5. One of the most dangerous aspects of the Google phenomenon is the widespread illusion that Google gives you Objective Truth. Rory talks to Ben Gomes, who is described as Google's Guru of Search, who talks about the Quest for the Perfect Search.

"The perfect search is giving you what you were looking for. Not just the words you typed - but what you were actually looking for."

The programme gave the impression that Google is converging on the Perfect Search. Rory himself says he generally finds what he is looking for. My own experience is that it sometimes requires a fair amount of ingenuity to find stuff, especially interesting and original stuff. See my posts You don't have to be smart to search here ... but it helps (Nov 2008) and Thinking with the Majority (March 2009). See also The Power of Twitter (April 2016).



Wondering about the deliberate spelling mistake in the title of this post? I wanted to pay tribute to a listing from @brightonargus.
Which reminded me of the original Argus Panoptes, the giant who would be the mythical ancestor of Google. And also the ARGUS-IS system, a secret rival to Google's Street View.  Even Argus may have flawed vision sometimes.

Wikipedia: Argus Panoptes, ARGUS-IS.

Leigh Alexander, Do Google's 'unprofessional hair' results show it is racist? (Guardian 8 April 2016)

Rory Cellan-Jones, Six searches that show the power of Google (BBC 26 April 2016)

Konrad Krawczyk, Google is easily the most popular search engine, but have you heard who’s in second? (Digital Trends, 3 July 2014)

Sunday, April 03, 2016

From Networked BI to Collaborative BI

Back in September 2005, I commented on some material by MicroStrategy identifying Five Types of Business Intelligence. I arranged these five types into a 2x2 matrix, and commented on the fact that the top right quadrant was then empty. 



 
The Cloud BI and analytics vendor Birst has now produced a similar matrix to explain what it is calling Networked BI, placing it in the top right quadrant. Gartner has been talking about Mode 1 (conventional) and Mode 2 (self-service) approaches to BI, so Birst is calling this Mode 3.




While there are some important technological advances and enablers in the Mode 3 quadrant, I also see it as a move towards Collaborative BI, which is about the collective ability of the organization to design experiments, to generate analytical insight, to interpret results, and to mobilize action and improvement. This means not only sharing the data, but also sharing the insight and the actioning of the insight. Thus we are not only driving data and analytics to the edge of the organization, but also developing the collective intelligence of the organization to use data and analytics in an agile yet joined-up way.

I first mentioned Collaborative BI on my blog during 2005, and discussed it further in my article for the CBDI Journal in October 2005. The concept started to gather momentum a few years later, thanks to Gartner, which predicted the development of collaborative decision-making in 2009, as well as some interesting work by Wayne Eckerson. Also around this time, there were some promising developments by a few BI vendors, including arcplan and TIBCO. But internet searches for the concept are dominated by material between 2009 and 2012, and things seem to have gone quiet recently.


Previous posts in this series

Service-Oriented Business Intelligence (September 2005)
From Business Intelligence to Organizational Intelligence (May 2009)
TIBCO Platform for Organizational Intelligence (March 2011)


Other sources

Gartner Reveals Five Business Intelligence Predictions for 2009 and Beyond (Gartner, January 2009). Dave Linthicum, Let's See How Gartner is Doing (ebizQ, May 2009)

Chris Middleton, Business Intelligence: Collaborative Decision-Making (Computer Weekly, July 2009)

Ian Bertram, Collaborative Decision-Making Platforms (Gartner 2011)

Wayne Eckerson, Collaborative Business Intelligence: Optimizing the Process of Making Decisions (April 2012)

Monique Morgan, Collaborative BI: Today and Tomorrow (arcplan, April 2012)
Tiemo Winterkamp, Top 5 Collaborative BI Solution Criteria (arcplan, April 2012)

Cliff Saran, Prepare for two modes of business intelligence, says Gartner (Computer Weekly, March 2015)

The Future of BI is Networked (Birst, March 2016)


Updated 21 April 2016 (image corrected)

Thursday, March 24, 2016

Artificial Belligerence

Back in the last century, when I was a postgraduate student in the Department of Computing and Control at Imperial College, some members of the department were involved in building an interactive exhibit for the Science Museum next door.

As I recall, the exhibit was designed accept free text from members of the public, and would produce semi-intelligent responses, partly based on the users' input.

Anticipating that young visitors might wish to trick the software into repeating rude words, an obscenity filter was programmed into the software. When some of my fellow students managed to hack into the obscenity file, they were taken aback by the sheer quantity and obscurity of the vocabulary that the academic staff (including some innocent-looking female lecturers) were able to blacklist.

The chatbot recently launched onto Twitter and other social media platforms by Microsoft appears to be a more sophisticated version of that exhibit at the Science Museum so many years ago. But without the precautions.

Within 24 hours, following a series of highly offensive tweets, the chatbot (known as Tay) was taken down. Many of the offensive tweets have been deleted.


Before

Matt Burgess, Microsoft's new chatbot wants to hang out with millennials on Twitter (Wired, 23 March 2016)

Hugh Langley, We played 'Would You Rather' with Tay, Microsoft's AI chat bot (TechRadar, 23 March 2016)

Nick Summers, Microsoft's Tay is an AI chat bot with 'zero chill' (Engadget, 23 March 2016)


Just After

Peter Bright, Microsoft terminates its Tay AI chatbot after she turns into a Nazi (Ars Technica

Andrew Griffin, Tay Tweets: Microsoft AI chatbot designed to learn from Twitter ends up endorsing Trump and praising Hitler (Independent, 24 March 2016)

Alex Hern, Microsoft scrambles to limit PR damage over abusive AI bot Tay (Guardian, 24 March 2016)

Elle Hunt, Tay, Microsoft's AI chatbot, gets a crash course in racism from Twitter (Guardian, 24 March 2016)

Jane Wakefield, Microsoft chatbot is taught to swear on Twitter (BBC News, 24 March 2016)


"So Microsoft created a chat bot that so perfectly emulates a teenager that it went off spouting offensive things just for the sake of getting attention? I would say the engineers in Redmond succeeded beyond their wildest expectations, myself." (Ars Praetorian)


What a difference a day makes!


Some Time After

Peter Lee, Learning from Tay's Introduction (Official Microsoft Blog, 25 March 2016)

Sam Shead, Microsoft says it faces 'difficult' challenges in AI design after chat bot Tay turned into a genocidal racist (Business Insider, 26 March 2016)

Paul Mason, The racist hijacking of Microsoft’s chatbot shows how the internet teems with hate (Guardian, 29 March 2016)

Dina Bass, Clippy’s Back: The Future of Microsoft Is Chatbots (Bloomberg, 30 March 2016)

Rajyasree Sen, Microsoft’s chatbot Tay is a mirror to Twitterverse (LiveMint, 31 March 2016)


Brief Reprise

Jon Russell, Microsoft AI bot Tay returns to Twitter, goes on spam tirade, then back to sleep (TechCrunch, 30 March 2016)



Updated 30 March 2016

Saturday, November 28, 2015

Predictive and Real-Time Analytics

I shall be chairing the @UNICOMSeminars Data Analytics conference next week. Exploring the Business Value of Predictive and Real-Time Analytics (London, 2 December 2015)

A lot of the obvious applications of real-time analytics are in fraud detection and predictive maintenance. I shall be talking about some of the things I’ve been doing recently in the retail and consumer sector, using rich consumer data to drive real-time personalized engagement with the consumer across multiple touchpoints. We have been exploring ways to combine real-time analysis of the consumer’s current state (e.g. current location, what products they are currently looking at, readiness to buy, etc.) with a rich understanding of what one might call the consumer’s “purchasing genes” – for example, do they like to spend a long time reviewing alternative products before purchasing, do they like to wait for a special offer or voucher before buying, or on the other hand do they like to be the first in their social network to have a given product. This is a lot more complex than simply putting them into a fixed number of “consumer segments”.

Based on this analysis, it is possible to select an appropriate “next action” – for example, selecting the appropriate banner to display to the consumer when visiting the website, or the right topic of conversation for a human customer services agent.

Thus predictive analytics are helping retail as it moves from omnichannel commerce (which joins up the buying transaction between the online and the physical world) to omnichannel engagement (which joins up all aspect of the relationship with the consumer).

Omnichannel Commerce
(Systems of Record)

joins up the buying transaction between the online and the physical world
Omnichannel Marketing
(Systems of Engagement)

joins up all aspects of the relationship with the consumer

Given the large volumes of data involved, and the reliance on legacy systems to produce and process the data, we are not yet seeing this analysis being completely done in real-time. However, there are some critical factors that have to be done in real-time. For example, as soon as the consumer buys something, our clients want to stop trying to sell it, and move to a post-sales scenario. (In comparison, even the great Google is still showing me advertisements based on what I was browsing three weeks ago. Fail!)

Over the next couple of years, as the technology gets better, the data scientists get even smarter, and the marketing people get more sophisticated, we may expect an increasing proportion of the analysis to be done in real-time, using machine learning as well as more sophisticated analytics tools.

Saturday, November 14, 2015

Towards the Internet of Underthings

#WearableTech #InternetOfThings Once upon a time, the wires in an undergarment merely provided structural support. Now, people may have all sorts of wires and wireless devices hidden under their clothing. Here are some interesting examples.

  • The Foxleaf Bra delivers cancer-fighting drugs through the wearer's skin.
  • The @tweetingbra reminds women to examine themselves. (?)
  • The Lumo Lift helps improve posture through app-enabled coaching.
  • Various manufacturers (including Clothing+, OMsignal and SmartLife) produce health vests and sportswear packed with monitors to track your heart rate, breathing rate and the amount of calories you've burnt.

We are now encouraged to account for everything we do: footsteps, heartbeats, posture. Until recently this kind of micro-attention to oneself was regarded as slightly obsessional, nowadays it seems to be perfectly normal. And of course these data are collected, and sent to the cloud, and turned into someone else's big data. (Good luck with those privacy settings, by the way.)

If a device is classed as a medical device, it will be subject to various forms of accreditation and regulation. For this reason, many device makers will be careful to avoid any specific medical claims, but devices that offer some health advice are considered a borderline area.

Another borderline area is hi-tech underpants that protect men from the evil rays allegedly produced by all those wireless devices. Especially the radiation from mobile phones. (Including the Bluetooth that links your underwear to your smartphone.) One brand of underpants that claims to use a mesh of pure silver to create a Faraday cage around the genitals has been banned by the UK Advertising Standards Authority from making any medical claims.

Or maybe you could just switch the whole lot off.



The Wearable Medical Device in Your Future…Is Now! (Marketing Research Association, 28 April 2015)
Jennie Agg, The hi-tech bra that helps you beat breast cancer - and other clothes that can treat or prevent illness (Daily Mail, 10 March 2015)

Sarah Blackman, Student designs cancer-fighting bra (Lingerie Insight, 10 Feb 2015) 

Britta O'Boyle, SmartLife clothing claims to make sure you never miss a beat (Pocket-Lint, 12 March 2015) 

Rob Crilly, Hi-tech pants "protect sperm from phone waves" (Telegraph 22 October 2014)

Julie Papanek, How Wearable Startups Can Win Big In The Medical Industry (TechCrunch, 19 Feb 2015)

Hannah Jane Parkinson, Lumo Lift review: posture-tracking gadget is a straight shooter (Guardian, 14 November 2014) 

Helen Popkin, Tweeting bra exposed: Genuine support or publicity lift? (NBC News 25 October 2013)

Meera Senthilingam, How a high-tech bra could be your next doctor (CNN, 11 May 2015)

Brendan Seibel, High-Tech Underwear for Adventurous Geeks (21 April 2010)

Mark Sweney, Hi-tech underwear advert banned (Guardian 13 August 2014)

Dan Sung, World Cancer Day - The Real Wonderbra (Wearable, 14 Feb 2015)  


Related Posts Have you got big data in your underwear (December 2014)

Friday, November 13, 2015

Weaving in three dimensions

A garment is essentially a three-dimensional object. And yet the most common way of producing garments is from flat sheets of material - for example cloth or leather - that can be cut into pieces and then sewn into items of clothing. So we have a complex interaction between two patterns - the weaving pattern on the cloth and the cutting pattern for the tailor.

Some clothing designers have started to experiment with 3D printers, producing amazing fashion dresses and accessories.

Designer: Danit Peleg
Designers: Francis Bitonti and Michael Schmidt


For more examples, check out designers like Continuum Fashion.

But these costumes are mostly monochrome, and made from artificial materials such as nylon. Great for catwalk or party, or even a fashionable beach, but not exactly everyday wear. So instead of 3D printing, what about 3D weaving, using traditional materials? Here's something in linen.

Designer: Chen-Hsiang Hu

The industrial designer Oluwaseyi Sosanya has developed a new 3D weaving method, which allows not only the exact shape and size of the garment to be varied to the exact requirements of the wearer, but also the qualities of the woven fabric. He has been experimenting with footwear, where the density of the sole can vary from one part of the foot to another.
"With this [weaving system] you can pre-programme the density. At the ball of your foot, you may want a denser material. Right at the arch of your foot, you might want a softer material. At the heel, you might want a denser material. You can have that in one go."

Furthermore, Sosanya's system allows the footwear to be customized to the wearer's requirements, from sports to orthopaedics.
"Your foot is completely different to my foot,” said Sosanya. “We walk different, our cadence is different. All of these things are factors which play into the performance of our footwear. Now with 3D printing, you can scan your foot and you can scan an insole or even a whole sole or the whole shoe at some point. The designer and the chiropodist can say that you need to remove some material here and you can correct your walking. You have all of these opportunities now where you can do customisation around footwear." 

Of course, there is some history here. According to Wikipedia, perforated paper tapes were first used to control looms around 1725, but this technology did not become widespread until Jacquard switched to punched cards around 1801.

Source: Wikipedia

And according to the New Testament, Jesus wore a seamless robe for his crucifixion. One source (repeated around the internet, and now here) argues that this indicates an early Palestinian form of 3D weaving.
"Completely seamless garments, like the one Jesus wore, were unique to Palestine. They were woven on upright looms that used two sets of vertical warp threads, one at the front and one at the back of a crossbar. The weaver would alternate his shuttle, which carried the horizontal weft thread, from the front part of the web to the back, 'thus creating a cylindric piece of fabric,' says one reference work. A seamless tunic would likely have been a rare possession, and the soldiers considered it a desirable one." (Watchtower, 1 July 2009 p22)

If we combine these ancient and modern innovations, we can conceive of a very sophisticated form of personalization, in which the pattern on the cloth can be perfectly aligned with the cut of the garment, regardless of the size and shape of the wearer, without wasting material. And the material can be reinforced at elbows and shoulders. And the whole garment can be woven while you wait. No more child tailors in Far Eastern sweatshops then.




Wikipedia: Jacquard loom, Punched card, Seamless robe of Jesus

3D-woven fabric creates organically shaped lamps that glow in the dark
(de zeen, 11 April 2014)

Oluwaseyi Sosanya invents 3D weaving machine (de zeen, 23 June 2014)

Alec Buren, Danit Peleg 3D prints entire ready-to-wear fashion collection at home (3Ders, 24 July 2015)

Simon Cosimo, Electroloom - the world's first 3D fabric printer - launches on Kickstarter (3Ders, 16 May 2015)

Simon Cosimo, Fashion designer adds a third dimension to apparel design with '3D weaving' (3Ders, 31 July 31) 

Shane Hickey, The innovators: the 3D weaving machine putting new heart into soles (Guardian 3 May 2015)

Tanya Lewis, 3D Printing Weaves Its Way into Fashion (LiveScience, 7 August 2013)

Robert Sullivan, Envisioning the Future of 3-D Fashion: Welcome to the Virtual Dressing Room (Vogue, 3 September 2014)

Sunday, November 08, 2015

How Soon Might Humans Be Replaced At Work?

#CIPAai An interesting debate on Artificial Intelligence took place at the Science Museum this week, sponsored by the Chartered Institute of Patent Agents. When will humans be replaced by computers in any given job?

As this was the professional body for Patent Agents, they decided to pick an example close to their hearts. The specific motion being debated was that a patent would be filed and granted without human intervention within the next 25 years. The motion was passed roughly 80-60.

At first sight, this debate appeared to be an exercise in technological forecasting. When would AI be capable of creating new inventions and correctly drafting the patent application? And when would AI be capable of evaluating a patent application, carrying out the necessary searches, and granting a patent. Is this the kind of thing we should expect when the much vaunted Singularity (predicted from around 2040 onwards) occurs?

Speaking for the motion, Calum Chase and Chrissie Lightfoot were enthusiastic about the technological opportunities of AI. They pointed out the incredible feats that were already achieved as a result of machine learning, including some surprisingly creative solutions to technical problems.

Speaking against the motion, Nigel Hanley and Ilya Kazi acknowledged the great contribution of computer intelligence to support the patent agent and patent examiner, but were sceptical that anyone would trust a computer with such an important task as filing and granting patents. Nigel Hanley pointed out the limitations of internet search, which is of course designed to find things that other people have already found. (As A.A. Milne put it, Thinking With The Majority.)

The motion only required that a single patent be filed and granted without human intervention. It didn't need to be a particularly complicated one. But even to grant a single patent without human intervention would require a change in the law, presumably agreed internationally. (As it happens, my late father Kenneth Veryard was involved in the development of European Patent Law around 25 years ago, so I am aware of the time and painstaking effort required to achieve such international agreements.)

But this reframes the debate: from a technological one about the future capability of computers, to a sociopolitical one about the possibility of institutional change. Even if some algorithm were good enough to compete with humans, at least for some routine patent matters, the question is whether politicians would be willing to entrust these matters to an algorithm.

There are also strange questions of ownership and rights. Examples of computer intelligence always seem to come back to the usual suspects - Google, IBM Watson, and their ilk. If the creativity comes from the large computer networks run by these companies, then the patents will belong to these corporations. When Thomas Watson said, "I think there is a world market for maybe five computers", he wasn't talking about billions of laptops or trillions of internet-enabled things, but the very much smaller number of major computer networks capable of controlling everything else.

Can we realistically expect AI to take over one small area of patent law without taking over the much larger challenge of cleaning up legislation? After all, a genuine superintelligence might well come up with a much better basis for promoting innovation and protecting the interests of inventors than a few ancient principles of patent law.

But perhaps here's the killer argument. As the volume of patent applications increases, the cost of processing them all by hand becomes prohibitive. So governments could be tempted by the cost-savings offered by a clever algorithm. Even though governments have a very bad track record at realising cost savings from IT projects, politicians can often be persuaded to think it will be different this time.

So even if AI patent activity turns out not to be as good as when humans do it, and even if it subsequently results in a lot of seriously expensive litigation, it could seem a lot cheaper in the short-term.


References


http://www.cipadebate.org.uk/

Steven Johnson, Superintelligence Now (How We Get To Next, 28 October 2015)

James Nurton, Could a computer do your job (Managing IP, 3 November 2015)

Wikipedia: Technological Singularity


Related Posts

The End of Google (June 2006)


Update

For the potential ramifications of robotic legal assistants, see Remus, Dana and Levy, Frank S., Can Robots Be Lawyers? Computers, Lawyers, and the Practice of Law (December 30, 2015). Available at SSRN: http://ssrn.com/abstract=2701092 or http://dx.doi.org/10.2139/ssrn.2701092. Reported by Aviva Rutkin, Artificial intelligence could make lawyers more risk averse (New Scientist 27 January 2016).

updated 28 January 2016