#Dependant on #dumb #data and is making #bad #choices? #Douglas #Adams

Data, Big Data, Artificial Intelligence

Clients don’t understand their customers, they just think they do!

It’s not for the lack of trying or spending millions on developing and building huge data systems, the problems are many but can be traced back to one simple thing;

“Data only describes part of the what is happening and almost nothing of the why, let alone what should be done to change the situation”

Clients have been sold that data gives them the answers and that big data will close the loop for them to understand the upstream and downstream thinking of their customers, WRONG.

Douglas Adams noticed the real problem

Douglas Adam’s said  “But even Amazon has only got part of the picture. Like real world shops, they can only record the sales they actually make. What about the sales they don’t make and don’t know that they haven’t made because they haven’t made them?” Douglas Adams “The Salmon of Doubt” by Permission of Pan Macmillan. That pretty much covers the problem if you extrapolate the thinking for Data Analytics, Big Data or even Artificial Intelligence based Data and Decision systems.

“Data is binary a yes or no (even complex views), it does not capture motivation, intention, desire, cognition, distraction or any other human reasoning or pattern”

child pretending to be robot data prentending to be truth
child pretending to be robot data prentending to be truth

A child pretending to be a robot just as data pretends to be the truth, he is a kind of robot and data is a kind of truth

A pure Data approach to understanding customers will provide the wrong data because data is an absolute and people are not. Even with Artificial Intelligence it only works from the starting point you give it, if any of the perimeters are wrong the whole data sample is wrong.

Guide to understanding Customers

  • Data, Big Data, Artificial Intelligence – Tells you what
  • People in target demographic – Tell you why

People in target demographic

User research answers the question Why have we not made the Sale? through the only people equipped to answer the question, consumers. This is not market research, its scientific without a predetermined agenda or outcome. User Research is a problem solving method that offers solutions by finding the right questions, finding the right people and asking the questions in a way that does not lead or direct the answers.

There are right questions and people to ask?

This may sound a little Adamsesque (if you ask the answer to Life, the Universe and Everything you get 42, because it the wrong question). Getting the questions or setup wrong is the real problem with an Analytics approach to a Diagnostic process. While it may be reasonably expected by a seller to directly ask, why didn’t a visitor become a buyer or register. Visitors may be asking themselves where am I? what does this do? this does not make sense, should that be happening? technology, why do I bother? Why has my screen gone pink? None of these “in mind” experiences are expressed in the data or even a consideration for the data schema design.

A visitors experience is not only defined by the online environment but they bring past experiences, desires and doubts about their current experience. Without these insights from research, it is difficult for clients to grasp potential problems, gain a good return upon their investment (ROI), innovate to fit the market and consumer needs or break into a new market sector.

Reasons that Data is Trusted and People are Not

It appears to come down to scale and a short sighted approach to costs. Buying an Analytics Solution appears to tick all the boxes, even if in reality it does not. While using Research Companies or in-house Research Teams seems expensive in comparison.

“The real trick is to understand you need both, you always did”

retro robot toys, not what you expect when you say robot today
retro robot toys, not what you expect when you say robot today

When I first started using Web Position Gold (the analytics tool), bought by Webtrends long before Google Analytics existed or the current proliferation of products promising the impossible, we used it to spot trouble only. We would then do some user testing in the area, working out possible failure scenarios, from there we would suggest two or three solutions and build them for A/B testing to see what worked and what did not. Everything was monitored and all the data from both analytics and user testing was collated into one final solution. Sometimes there was a single resolution, a re-architecting of a section, in one project I kept 16 pathways active because they all delivered transactions for different types of customers.

The thing is just as there is no absolute way to find out the problem, resolution or adaptive innovation except byDiagnostics a digital and human activity.

Diagnostics

[Data+Human+Solution+Testing=Resolution]

+

[Feedback+Data+Human=Adaptive Innovation]

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#Cognition #Clash in the #IoT #SXSW

Thank you to everyone who attended our (Karl Smith and Thom Heslop) talk at SXSW, it’s the start of a long road into a really complex and contextual problem. But being silent in the crowd as the King walks by with no clothes on is not an option, peoples lives, futures and prosperity is at risk, not to mention the risk of multi-trillion dollar lawsuits that can follow by knowingly distracting people who are engaged in critical tasks.

Cognition Clash in the IoT at SXSW16
Cognition Clash in the IoT at SXSW16

The IoT – Internet of Things (Ubiquity) is the next great opportunity for commerce to engage with business enterprises and customers. However, there is no unified approach to the mental load between physical interaction, mental interaction and digital interaction. This cognitive landscape is inhabited by associated experiences that gel human behaviour and machine interfaces through, touch, mouse and keyboard. The usage of sight, voice and thought create new complexities and risks which have until recently been the subject of defence technologies (battlefield and strategic), where clear outcomes and prescribed mental models exist.

IoT clash girl dies
IoT clash girl dies

The diversification of these touch points and multi-point human logic models clash and derail human thinking patterns.

We are looking for people and their knowledge to help create an Ubiquity Open Standard. We are doing this because no one else has noticed this fundamental error in thinking, the hoping that product based companies will work together in creating common standards that are driven by an understanding of human thinking capabilities, cognitive models, relational thinking and machine interactions is unlikely.

While product manufactures continue with supremacy attitude to other ecosystem products and services,

“the human voice and our needs and desires are subjugated to simply another component”

albeit the one that is constantly paying for everything without any input on how it works.

Some Foundations (the rest will go in a technical paper)

Distributed Cognition studies the ways that memories, facts, or knowledge is embedded in the objects, individuals, and tools in our environment. According to Zhang & Norman (1994), the distributed cognition approach has three key components: Embodiment of information that is embedded in representations of interaction Coordination of enaction among embodied agents. Ecological contributions to a cognitive ecosystem.

In Embodied Interaction Dourish -everyday human interaction is embodied; non-rationalising, intersubjective and bodily active.  User, not designers, create and communicate meaning and manage coupling. Not just concerned with what people do, but also with what they mean by what they do and how that is meaningful to them. It reflects the sets of meanings that can be ascribed to objects and actions over those objects as part of a larger task or enterprise

Cognition the key to the mind, how people understand what they can do is by comparison a Diagnostic Methodology (goals, adaptations, conventions) with what they already know by accessing the Active Narrative patterns they have created in their own minds according to Smith (2005).

Cognition Patterns Cognition Clash in the IoT different people think differently
Cognition Patterns Cognition Clash in the IoT different people think differently

Cognition Groups create a communication paradigm, they carry intention, meaning, risks and benefits.

  • Some Cognition patterns are common, shopping basket etc.
  • Some Cognition Patterns are social by Family, Sports Team etc.
  • Some Cognition Patterns change without notice

Guided Interaction, existing websites offer guided interaction – simplified cognitive pattern encapsulating a plethora of interacting technology and data systems: Shopping Basket – This representation allows for distributed cognition > appropriation > cognitive pattern forming understand– once a user has used a shopping basket they will understand how to use them and generalize: transferable cognitive pattern

Some of the issues with the IoT

  • There is no standard of interactivity for humans in the IoT – not a problem if passive background machine-to-machine. A very big problem if actively interacting with humans, who are all different and can create their own meanings for example LOL.
  • How does a user form any cognitive patterns from an invisible system?
  • IoT combines known patterns as hidden machine-to-machine communications that can create mistrust and security fears
  • Detailed component view we have constructed around daily interactions is no longer valid

Some of our initial research

IoT Design Principals

  • What is device / service for?
  • Where will it be situated?
  • When will it be triggered?
  • What other devices will it be interacting with?
  • Where can it clash?
  • Security? – * Lack of security – Shodan
  • Design Principal: “Do No Harm

IoT Design Risks

Context is critical

  • Situational interaction problems for consideration

The following barriers reduce our ability to understand the situation

  • Perception based on faulty information processing
  • Excessive motivation – over motivated to the exclusion of context
  • Complacency
  • Overload
  • Fatigue
  • Poor communications

A possible solution

  • Avatar (can be visual, sound, texture, smell, taste or a combination) – smart use of Artificial intelligence (AI), where the users cognitive interface is patterned on their unique cognition pattern through a learning algorithm
  • This avatar should be directional and instructional like digital signage
  • This avatar should respond to the users behavioural interaction and should fall away gracefully as users behaviour becomes more ‘expert* In effect it should be a learning system – learns from the users rather than based on static rules
  • For example the AI that George Hotz has built into his self driving car while not the answer points to the kind of thinking required to find the answer, don’t tell the machine to watch and learn from a human and then carry out your task (from 3.33 to 5.04) “the point is to drive naturally like a human, not some engineer’s idea of safety“. For anyone who then thinks this is the final solution, please let us know why you think driving a car is like cooking dinner or navigating the street?

The Full SXSW Talk is on YouTube

Connect to the speakers on LinkedIn here Karl Smith and Thom Heslop

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#Cognition #Clash in The #Internet of #Things

I’m speaking at SXSW Interactive 2016 on Cognition Clash in The Internet of Things, if your in Austin, TX let me know?

The IoT is the next great opportunity for business enterprises to engage with customers. However there is no unified approach to the mental load between context of use, physical interaction, mental interaction and digital interaction. This cognitive landscape is inhabited by associated experiences that gel human behavior and machine interfaces through, touch, mouse and keyboard. The usage of sight, voice and thought create new complexities and risks which have until recently been the subject of defense technologies, where clear outcomes and prescribed mental models exist. The diversification of these touch points and multi-point human logic models clash and derail human thinking patterns.

http://schedule.sxsw.com/2016/events/event_PP47495

Hashtags: #sxsw #IoTdesign

Sunday, March 13
12:30PM – 1:30PM

JW Marriott 
Salon FGH
110 E 2nd St

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