Gamification to change business incentives

Gamification is gaining more momentum. Link with AI Virtual Agents inevitable!

Source: http://tiny.cc/vklxc Guardian

Author: Cath Everett

Date: 27 June 2011

Key extract

"Gartner named it among the top CIO trends to watch and predicted that more than half of organisations wanting to encourage innovation would 'gamify' their supporting processes by 2015.

Brian Burke, a Gartner analyst, defines it as taking one of the four main computer gaming techniques and re-applying them to a non-games environment.

The first comprises accelerated feedback cycles. These are necessary to maintain motivation and engagement but contrast with real world situations where feedback, for example in the shape of annual performance appraisals, is often slow.

The second is setting clear goals and having well defined rules of play to ensure that users feel able to achieve the objectives. The third is about creating a compelling narrative to encourage individuals to get involved and hold their interest.

The final must-have is ensuring that tasks provide participants with continual challenges that are neither so testing that they are discouraging nor so easy that people lose interest. The ideal is to include multiple short term, achievable goals in any given system or process.

As to the point of all this, James Riley, managing director at digital marketing agency Effect, says it is to create "fun in things that traditionally weren't by playing to human nature. So what you're really trying to do is to create an experience that people engage with emotionally – that's when you get real success".

The gamification concept has to date been employed mainly for marketing by business-to-consumer companies, particularly within social media. The objective is to make it more enjoyable for consumers to interact with their brands in a bid to foster loyalty.

But both Riley and Burke believe expect gaming techniques to make their way into all kinds of areas, ranging from training and innovation to boosting employee performance and engagement. With this in mind, Burke advises IT directors to try and get some hands-on experience as soon as possible so they can educate business colleagues and work with them on evaluating possible opportunities.

"Gamification is set to become an important trend, impacting many areas of business and society. I believe that game mechanics are going to have a huge impact on the way organisations engage stakeholders, innovate and evolve, and we are just on the leading edge of that trend," he says."

Can you trust your CIO with the Cloud?

I have produced a video covering Can you trust your CIO with the Cloud? http://tiny.cc/znd2k

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My Current Work

I am currently working on developing a blueprint for an Adaptive Enterprise powered by a knowledge exchange. The blueprint starts with a sense-and-respond maturity model with level 1 being a silo organisation and level 2 being a network-centric organisation. There are a further three higher levels. Knowledge is the crucial dynamic for an adaptive organisation with its highest form being knowledge for decisioning. Supporting the human systems is the challenge as automation is relatively a lot easier. Changing cultural behaviour is a key element and thus using advanced forms of corporate gamification and ‘wisdom of crowds’. The top levels of the sense-and-respond maturity model link with my work on artificial intelligence for natural and decision-tree language. The Cloud has collapsed the technology costs needed to support a sense-and-respond model so practical solutions are a lot easier to accomplish

New technology will enable face recognition to be applied to social networks like Facebook.

Upload your own photo and then search for all instances ...

This will have a big impact upon social media.

The implications to privacy are huge but that will not stop it from being used in the mass market.

It is already being used to find lost friends that have published photos with your face in it.

The Red Cross seems to like the idea for finding people.

Ad people now have new inventory.

Find out more and go to http://face.com/

2010 is the start of Web 4.0

2010 is the start of web 4.0 Artificial Intelligence Complementing Humans.

Why?

72% customers want more self-service and self-sufficiency. Virtual Agents are now having around 40 million conversations a month as representatives for major corporates like Ebay, SFR (Vodafone) and Comcast.

Why?

The benefits are very compelling. Virtual Agents are at least 12 times lower in cost compared to Human Agents.


My Action

Launch the leading Virtual Agent Platform.

Freddie McMahon

I use my Twitter to broadcast tweets about customer experience http://twitter.com/cepractice

AI 169 Insects are being converted into cyborgs – the scientific challenge is handling the power for the cybernetics; ethical issues could be huge

"Cyborg insects" (using remote-controlled or chip-based neural stimulators to control movements) could be powered by piezoelectric strips attached to their backs (generating 10 millivolts per fiber in in a proof-of-concept experiment), Tokyo University of Agriculture and Technology researchers have found.

Powering these "stimulator chips" is a big limitation. "Wires from an external power source restrict their motion, and most battery cells are too heavy and wouldn't fit on the insect," says Keisuke Morishima from the Tokyo University of Agriculture and Technology in Japan. Smaller batteries have been used, but run down in as little as a few minutes.

Instead, Morishima suggests that the insects themselves could power the slave-driving chips. As a proof of concept, he glued a piezoelectric fibre - 4 centimetres in length but just 200 micrometres across - to the back of a Madagascar hissing cockroach. As the cockroach walked, each step stretched and squeezed the piezoelectric fibre, generating electricity via mechanical stress.

His experiments show that the cockroach's movement can generate more than 10 millivolts in a single fibre. About 100 of these fibres would be enough to power the stimulators, he says (Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology, DOI: 10.1016/j.cbpb.2008.09.055).

Kevin Warwick, a cybernetics expert at the University of Reading in the UK, thinks it may be difficult to store the generated energy in order to provide a steady supply throughout a cyborg insect's mission. He also thinks this number of fibres may be too heavy for the insect to carry. "I'm quite sceptical of the leap to using this as a power supply," he says.


However, Warwick says the method may be more easily applied to larger animals like rats, which could generate greater power when controlled using a similar system.

AI 168 EXPERT SYSTEMS versus DECISIONALITY DECISION-TREES

EXPERT SYSTEMS

Primary Argument

The average life expectancy of an Expert System was 18 months as the inference engine weakness was that it lacked ‘human’ judgment to ‘know’ when to stop learning. As a consequence, it over learnt leading to decisioning distortions that are typically not obvious at first but then rapidly deteriorate. The problem was further exasperated as the Expert System is ‘black-box’ AI, which means there was no transparency of how decisions were made. The legacy of this issue has become more topical recently in the wider area of AI related to trust and ethical risks.

Secondary Argument

Knowledge acquisition required the coming together of two specialists: subject matter experts and knowledge engineers to develop the data and inference procedures. This created interpretation issues, plus high costs and elapsed time for knowledge acquisition.

Other Arguments

Wikipedia http://en.wikipedia.org/wiki/Expert_system/ summaries Expert Systems strengths and weaknesses quite well as:

Strengths:

• Provides consistent answers for repetitive decisions, processes and tasks
• Holds and maintains significant levels of information
• Encourages organizations to clarify the logic of their decision-making
• Never "forgets" to ask a question, as a human might

Weaknesses:

• Lacks common sense needed in some decision making
• Cannot make creative responses as human expert would in unusual circumstances
• Domain experts not always able to explain their logic and reasoning
• Errors may occur in the knowledge base, and lead to wrong decisions
• Cannot adapt to changing environments, unless knowledge base is changed


EXPERT SYSTEMS DECISION-TREES

Expert Systems use data driven Decision-Trees for forward and backward chaining. However, it is the use of data driven Decision-Trees combined with inference-based learning that led to the weakness of Expert Systems.

The use of Decision-Trees is fundamental to IF-THEN-ELSE so an alternative approach was needed that bypassed the weaknesses of Expert Systems.

DECISIONALITY DECISION-TREES

Many concept and technology challenges had to be overcome to provide an alternative set of technologies to Expert Systems.

One over riding challenge was that the tools had to be simple and natural to use. Though this has been achieved it does create the perception of familiarity from the past and being so simple how can it be any good.

This is our oxymoron as the technology is very simple to use but at the same time it can cope with the velocity, volatility and complexity of procedural knowledge.
Procedural knowledge is about IF-THEN-ELSE logic. Decision-Trees are a natural visualization for this type of logic. Of course, knowledge cannot be contained in one Decision-Tree. So by treating knowledge as a collection of Decision-Tree objects which can be linked enables an ecosystem to be created that can cover any breadth and depth. Indeed, this ecosystem of knowledge objects can grow and evolve without constraint.

This is quite a challenge as software convention is that the bigger a system becomes the more complex it is too build and there is a tipping point where it becomes untenable. Yet the ambition to cover all procedural knowledge that can continually evolve demanded a software solution that would have to be different. We solved this by:

• Automatically generating a stateless web-service from the Decision-Tree script – this means no database is used which is the opposite of an Expert System.

• Enable the Decision-Tree script to dynamically link with a web-service that required a handover to a different knowledge set.


This combination enables creation and change to happen at the ‘speed of articulation’ thus supporting the development of an ecosystem that can change and grow as fast as is needed.

At the same time this approach solved another problem and that is the usage of the knowledge. People only want to navigate down the pathways of their choice without having to be exposed to the landscape of the knowledge. We have found that knowledge interaction can go deep very quickly at the rate of say a step every 5 to 8 seconds.
This approach means the only limit to the number of pathways and outcomes that can be interacted with is a constraint of the Decision-Tree scripting and not a constraint of the technology.

Because we can automatically measure the interaction in terms of steps, flows, patterns and metrics the learning loops can be very fast but they are human controlled. This whole approach is white-box.

The combination of capabilities provides a sound foundation for the acquisition, application and usage of procedural knowledge that can be accessed by any connected device or application.

The DecisionFlows scripting tool embraces visualization, narration and simulation. It is designed to improve logical thought and the acquisition of knowledge.

The Decisionality Decision-Trees use forward and backward chaining techniques as do Expert Systems. The difference is Expert Systems are data driven whereas the Decisionality is driven by human interaction.



Here are some other points for consideration of advantages between Decisionality Decision-Trees over Expert Systems:

1. Decision-Trees are simple to script whereas an Expert System needs a knowledge engineer thus creating a skills shortage plus overheads for knowledge capture from subject matter experts.

2. Decision-Trees are an open system as it is easy to link the end of a pathway within a Decision-Tree to the start of another pathway in another Decision-Tree. An Expert System is a closed system as it is constrained by the design of its inference engine and application.

3. Decision-Trees are simple ‘natural’ programs that can adapt to complexity and chaotic conditions. Expert Systems are designed to cope with a complicated system, but have difficulty coping with the dynamics of complexity and chaos. (20 years validation Stephen Wolfram New Kind of Science).

4. Decision-Trees are stateless whereas Expert Systems are data driven, which has an embedded complexity cost as more data items are developed and used.

5. Decision-Trees are a white-box meaning it is transparent, simple to understand and interpret. People are able to understand Decision-Tree models and therefore are designed for organizational retention of knowledge. Expert Systems are a black-box that is complex to understand and has greater reliance upon tacit knowledge of a specialist that dilutes overtime.

6. Decision-Trees can have value very quickly even with a small number of nodes. Important insights can be gained from usage that often stimulates ideas for knowledge evolution that were not obvious at first. Expert Systems in comparison evolve slowly and to the point of decision contamination.

7. Decision-Trees can be created by subject matter experts without the need for software specialists as with Expert Systems.

8. Decision-Tree dynamic linking generates an exponential growth of pathways and outcomes compared to a far slow rate from Expert Systems that will then reach a plateau without further advancement being made.

9. Decision-Trees development enriches inductive and deductive reasoning as it focuses upon pathways and outcomes. This value is largely diluted with Expert Systems as it is in the hands of the knowledge engineer and not the subject matter experts.

10. The interactive use of Decision-Trees, via web-services, and the automated analyses of interactions provide short learning loops enabling Decision-Trees to be evolved rapidly based on behavioral insights. Expert Systems capabilities weaken overtime as mentioned.

11. The reuse of Decision-Trees and dynamic linking of Decision-Trees (via web-services) increases value overtime enabling exponential growth of pathways and outcomes in very short time frames.

12. Decision-Trees with stateless web-services do not create legacy systems unlike Expert Systems.

13. Expert Systems decreases in value overtime whenever there are high rates of complexity, velocity and volatility. The opposite is true for a Decision-Tree ecosystem.

14. Decision-Tree scripts have been extended to influence behaviour of usage so that other mediums like pictures can be used to influence decisioning. This is accomplished because of event-tags being available for each scripted step. This level of granularity is not available from Expert Systems.

15. As the Decision-Tree generates a web-service this can be accessed across all digital touchpoints. Expert Systems do not typically have this level of interoperability.

16. The construction of the Decision-Tree is simply not just focused on business logic but on good dialogue and choices to influence behaviour and decisioning. The automated analyses of behaviour enable the Decision-Tree to adapt to behavioral dynamics. Additionally, dialogue narrative can change according to pathways chosen. Expert Systems have limited capabilities for the nuances of different behaviors.

17. Decision-Tree source and its web-service representation are measurable as a knowledge asset. This is not the case with Expert Systems.

18. Decision-Trees can be developed in parallel with each one often being built in a matter of hours. Therefore the speed of building an ecosystem from existing procedural knowledge is very fast.

AI 167 MS&V is regarded as high growth sector within the current economic climate

The relatively new industry of modeling, simulation and visualization (MS&V) comprises numerous planning, analysis and training tools made possible by sophisticated computing. These tools can suggest and test concepts, minimizing reliance upon trial and error, and they can present information in ways that enhance comprehension.

For example, the tools might teach a medical student how to perform a surgical procedure without putting an actual patient in harm's way. Other applications are seen in simulations to test aircraft designs, in vehicular traffic models to simulate — and improve — flow along highways, in video games to teach algebra, and in models to predict the performance of a soldier or an athlete. Artificial intelligence, robotics and virtual environments also are part of MS&V.

AI 166 Big Stage launches a “Portable You” avatar for integration into 3rd party solutions

Big Stage Entertainment (for previous references go to AI 129 and AI 56) announced today the launch of its "Portable You" program, which opens up its 3D facial modeling system to third parties for integration in games, virtual worlds, websites, mobile apps, and more.

The first announced partner is Icarus Studios, which will integrate the system with its virtual worlds’ platform.

Virtual event solutions provider, The Venue Network, already plans on adopting the face creation tools for its customers, allowing them to network with their own animated, lip-synched faces.

“Given the complexity of human faces, developing high-fidelity, realistic facial construction systems for avatars is incredibly costly and requires highly specialized skill sets,” said James Hettinger CEO, Icarus Studios. “PortableYou” offers an easy and cost-effective way for us to integrate sophisticated cloning capabilities into the virtual worlds we create. Our clients are very excited that their users can now create accurate virtual representations of themselves for use in their worlds, at development costs that generate significant ROI for incorporating the innovation in user experience that the PortableYou system make possible.”
Portable You includes APIs, code samples, methods and reference libraries for customization.

“By offering a powerful, unified system for the integration of a realistically animated 3-D version of yourself into your digital life, PortableYou has the potential to revolutionize how we both entertain ourselves and communicate through digital media,” said Phil Ressler, Big Stage Entertainment CEO. “With the high level of personalization that PortableYou makes possible, digital media can evolve to truly reflect who we are in the real world, whether through life-like extension or alter ego fantasy. Faces are fundamental to human communication and adding recognizable, animated avatars to an application changes it fundamentally."