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Research visit to California

goletaI (Nava) have just come back from a fantastic trip to California, supported and enabled by the generous SICSA PECE grant to visit the Four Eyes Lab at the University of California Santa Barbara (UCSB) and Dr. John O’Donovan.

During my time at the 4Eyes lab I learned more about interactive visualizations, and we designed a user interface that contributes to the discovery of novel and relevant content, and improves perceived transparency and control. With Jay Byungkyu Kang, Tobias Höllerer and John O’Donovan at UCSB we worked on a submission for the workshop on interfaces and human decision making for recommender systems (IntRS) in conjunction with the ACM Recsys conference in Vienna. We are currently improving on this work in a system that uses live twitter data.

system-mockup1

The submission, titled Inspection Mechanisms for Community-based Content Discovery in Microblogs”, was accepted for publication.

I also visited and gave invited talks at Yahoo! Research (Sunyvale), and InTouch Health (Goleta).

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Dishonesty paper published

The possibility of dishonest statements and dishonest behaviour is something we all have to be aware of. A particularly interesting question is how to let computers reason with this. This is less far-fetched than it may seem. After all, the Turing test (one of the basic cornerstones of Artificial Intelligence) is based on a computer successfully convincing someone he’s in fact a human. Apart from that, truly intelligent systems may want to have ways of detecting, dealing with and reasoning about the kind of dishonesty they may encounter during some of their interactions with humans.

In the recently published published paper “a formal account of dishonesty” we give a logical formalisation of different types of dishonesty, including lies, bullshit and half-truths. We study the logical properties of these, and provide a number of maxims that we feel every intelligent system that faces the possibility of dishonesty should adhere with.

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Invited talk at Centre for Human Computer Interaction Design London

On the 13th of February Nava gave a talk at HCID at City University London: Evaluating the Visualisation of Plans in the SAsSY Project (Talk slides)

Screen shot of first slideAbstract: The Scrutable Autonomous Systems (SAsSy) project aims to enable the scrutiny of autonomous systems by allowing agents to generate plans through argument and dialogue, while justifying the purpose of each step within the joint plan. Humans or agents can then critique these plans by suggesting and justifying alternative courses of action as needed, thus driving the planning process. However, this requires the system to first present the plan that has been chosen for execution by the system to the user. Given that these plans are often long and complex, one key challenge of providing transparency to humans regarding the internal workings of an intelligent system is therefore (good) information presentation. One of the challenges has been to decide how to adapt the plan presentation to a user’s role and area of responsibility. This talk addresses a key question of how to address the “goodness” of an adaptation. It describes a layered-evaluation approach, measuring performance in a dual task effectiveness) to complement measures such as time to complete (efficiency), and self-reported measures. This talk describes two case studies evaluating visualisations of a plan that illustrates the value of the approach.

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Nomination Best Paper Award

A technical paper explaining part of the reasoning model underlying the SAsSy demonstrator has been nominated for the best paper award at the 2014 Benelux Conference on Artificial Intelligence (BNAIC). The paper shows the correctness of the some of the proof procedures applied in the demonstrator. Although the actual prize was awarded to another paper of the conference, we feel that the fact that our work was among the nominees acknowledges that we’re on the right track.

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DEMOfest Edinburgh

Roman Kutlak presented the SAsSy demo software at DEMOfest organised at the University of Edinburgh. DEMOfest is an event that brings together scientists, industrialists and investors to take cutting edge projects and applications to the next stages of development. The event covers many themes such as robotics, human computer interaction and natural language processing. It is a great networking event that helps to bring science to everyday life and we are happy to have been able to take part in it.

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Videos: Adapting plan presentation, filtering and highlighting

 

One of the strands of research in SAsSy is how to adapt the presentation of plans to users depending on their interests or areas of responsibility. We have been looking at the use of highlighting and filtering for this. Our method works for both text and graphs, and considers that some tasks need to be done before others (dependencies).

I demonstrate how we do this in the current version of the system here:
screen shot of a planPart 1: Highlighting (mp4, 5.33)
Part 2: Filtering (mp4, 1.30)

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Which forecast should I trust? Is it going to rain tomorrow?

 

What if I showed you this story?
Screen Shot 2014-06-06 at 11.33.12
The weather forecasting service of the broadcasting company AAA says
that it will rain tomorrow. Meanwhile, the forecast service of the broadcasting
company BBB says that it will be cloudy tomorrow but that it will not rain.

Screen Shot 2014-06-06 at 11.33.21

Hard to decide which one to listen to, right? (Especially when it comes to weather that is so unpredictable anyway.)

But what if I also told you that:
It is also well known that the forecasting service of BBB is more accurate than the one of AAA.

You might develop a preference for listening to BBB’s forecast. If that is the case, then you might also say that it will not rain tomorrow.

Why is this interesting? Well, argumentation theory looks at how we reason over conflicting statements. So like where AAA and BBB are saying two things that cannot both be true. The theory predicts what points of view are “logically” correct. There are different flavors of the theory though, many of which do not consider preferences.

So a theory that does not consider preferences would say that you would still be undecided even if you knew BBB was more reliable. But we felt pretty sure that people use preferences when they make up their mind about these sorts of things. And we knew of a way of representing statements like this in a logic with preferences (thanks to Henry Prakken and Giovanni Sartor).

And indeed this is what we found. People make the conclusion you would predict if they used preferences. Not only that, but they also said the preference statement was information they thought was relevant when they made up their mind.

We found this was the case for weather, but also for other domains like a car sale, and regional independence!

You can see the stories and the logical representation behind them here.

Not too surprising of course was that more people were undecided for weather than in the other domains, but they still used the preference information and decided that it was not going to rain!

My colleague Federico is going to present this paper at the European Conference of Artificial Intelligence in Prague this summer, but you can have a look at it now too.

But just in case, do not forget your umbrella!

umbrella

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by | June 6, 2014 · 10:41 am