Model of Human-Machine Trust Dynamics

Another piece that was developed as part of my Ph.D. candidacy advanced examination.  This artifact was created while addressing the dialogue that takes place between automated systems and human operators and the cycle of trust evolution that results.  The illustration presumes that trust updates based only on positive and negative experiences (as has been previously shown).  This illustration is important to highlight the varied effect that delayed feedback can have on attitudes of trust; however it is greatly simplified in that it does not consider additional factors that could influence the degree of change when receiving feedback on one’s decision to rely.  For example, I would hypothesize that the degree of risk associated with relying on the system and the perceived separation between expected performance and actual performance represent two factors that would also likely play into the degree of influence that receiving feedback on one’s decisions could yield.

Framework of Trust and Reliance in Automation

As part of my Ph.D. candidacy I was required to take an Advanced Examination where each student receives individual questions based on his or her intended dissertation topic.  The questions are intended to motivate the student to learn about areas that his or her advisers feel are gaps in the student’s understanding of the problem domain or dissertation method.  The questions are very theoretical and typically require (very long) written responses based on extensive literature reviews to formulate logical responses.

For my A-Exam, I received 5 questions (some with multiple parts) and was required to respond to them in a 2 week period (pretty standard for my department/major combination).  At the time of my A-Exam my intended focus was on dynamic trust in automated systems so one of my questions was to characterize the effects that real-world dynamics are likely to have on human trust and reliance in automated systems.  Luckily, I bounded this discussion within the domains of intelligence analysis as it served as  perfect test bed for both my intended dissertation focus and for highlighting the factors that influence trust and reliance.

(click to enlarge)

Incorporating situationally qualified human observations into a fusion process for intelligence analysis

Since my second year at UB my research assistantship has been funded by a 3 year multi-university research initiative (MURI) grant focused on network based hard/soft information fusion.  The first year of this research (for me at least) was focused on learning about how accurate people are at observing different phenomena in the world given specific contextual factors.  For example, how accurately can people judge distances?  What if it’s nighttime?  What if it’s snowing? etc.

This work was developed to allow human observations to be appropriately characterized in terms of their error/bias so that they could be integrated into a data fusion process along with hard data (which comes from things like radar sensors that are highly calibrated).  The poster below, which was created for a UB School of Engineering and Applied Sciences poster competition, describes the results of these research efforts at a high level.

Procrastinate

I have found myself lacking motivation to focus on my academics lately.  I attribute this to a sense of (temporary) closure to many arcs of my research work.  For example, my joint research on qualifying human observation accuracy was recently presented at the CogSIMA conference in Miami Beach.  So rather than get back into work that was started a while back (or work on my dissertation proposal which still needs a defined topic) I decided to create the “Son of Grumm” paper toy seen above.  Ironically he is standing on a paper that I should probably have been reading instead.

I got the template for the model from an amazing book I picked up at Urban Outfitters on sale.  Grumm isn’t the first model I’ve created, but he’s my favorite so far, especially because he didn’t have any curved cuts.  I find that putting together these models is quite enjoyable; it’s a nice combination of relaxing + rewarding (when you’re done).  My next step is to assemble the Howl’s Moving Caster model; however, I’m also reading up on creating my own models using pepakura designer freeware.  I’ll need to come up with a good idea for what to design first though.   I also think that from a usability/human factors standpoint, if I can get this software to work out well it could become a useful tool for rapid prototyping of 3D objects.   Excelsior!

Back to reading the paper for now though – Son of Grumm has taken his spot guarding my trackball.

Pepakura + Howl’s Moving Castle = Huge $$ Savings

Ever since I saw Hayao Miyazaki’s movie Howl’s Moving Castle I have wanted a model of the amazing moving castle itself.  I even was lucky enough to find one in the bathroom of a bar in Japan I visited (“darts”) and saw that the models that japanese artisans created for their anime movies were quite amazing.  The problem with these models however is that they cost around $600 for even a small model of the castle on eBay and even more from specialty shops.  Subsequently, my original searches for a decent sized castle model left me with only a sense of failure and disappointment…. until recently.

I was browsing the internet for paper cranes (I think that was it at least) and I stumbled across the world of papercraft, aka pepakura.  Papercraft is essentially just paper models that you cut out pieces to and then fold (and sometimes glue) to assemble.  Ironically, I have 8 papercraft models of various random figures/monsters sitting on my desk that I’ve created and custom software that lets you design papercraft models using Solidworks files you create; however I never thought to look up more intricate model templates for download.  Anyways, while I was reading up on pepakura I came across the holy grail i’d been searching for – a large scale (26 pages of full-color pieces) model of Howl’s Moving Castle.  To my great delight the model appears to be a fairly decent scale, is full color, and is (in my opinion) even better than the $600 resin models you can purchase.  The best part?  Building the model myself will make it all the more enjoyable (and the download was free).

So i’ll be starting into my Moving Castle Papercraft next week hopefully (decided to have the parents print the 26 pages of color so I could get it on cardstock and not destroy my color ink cartridges).  I’m sure i’ll document the process and hopefully add a follow-up post once its complete.  Also, if you’re interested in creating one yourself you can download the PDF template for free (just Bing it) or shoot me a message and i’ll send it to you myself.

Design of an eTextbook

This project was completed as a requirement for cognitive engineering course in my Ph.D. program.  It was a team project focused on developing early design requirements for an eTextbook (i.e., a digital solution to physical textbooks).  Because of the many tasks that current physical textbooks support (e.g., annotation, bookmarking, highlighting, etc.) and the many different ways students (and faculty) interact with them, our team adopted a work domain analysis to develop an abstraction hierarchy.

Work domain analysis is part of the cognitive work analysis (CWA) methodology which is unique compared to more traditional engineering methods as it focuses on identifying the requirements, constraints, and affordances for cognitive work in a domain.  CWA was originally proposed by Rasmussen et al. (1994) and further refined by Vicente (1999) as a means to support the design of complex systems that would be more adaptable under unanticipated operating conditions.   Since its original application to the design of process control systems, CWA has been adapted and successfully applied to other complex domains and systems.  Across these domains and systems, CWA has effectively been shown to support the design of novel interface displays through its ability to produce models of work objectives combined with constraints and affordances that inhibit or support those objectives.  Additionally, as Bisantz and Roth (2003) illustrated, CWA is particularly effective for design of novel systems requiring adaptability based on unanticipated domain conditions.

The final report generated by my team, along with a design process overview and final recommendations, can be viewed below.

Rah doe kankee kung (aka my kind of scum)

A simple formula for winter success…

Gravy Master was key here as this amazing snow sculpture actually smells like what I’d imagine Jabba the Hutt would smell like – fatty old gravy.  Unfortunately, this seems to be Tom Brady’s (my dog) favorite flavor of snow cone.

Next up, either a Rancor, R2-D2, or the Sandworm from Dune.

Lego + Star Wars = Christmas Perfection

For the 3rd year running i’ve gotten Star Wars Legos sets as Christmas presents from my awesome girlfriend.   This year I got two of my favorities (tough competition with the Sandcrawler) the Tantive IV and Slave I.  Han Solo frozen in carbonite is one of the best minifigs I’ve got and I now have 3 sets of R2-D2 and C-3PO.

The Tantive IV was the larger set, but the Slave I is top notch in terms of details and actionable components (e.g., firing missiles, dropable depth charges, etc.), plus the Boba Fett character is key with jetpack + cape.

Classic IE for the Win.

With my first dissertation committee meeting behind me, my latest research project all written up and submitted to CogSIMA 2011, and my consulting work in a momentary lull I’ve found myself without any pressing deadlines to motivate a strong focus on work.  The result of this state is a shift towards finding little problems to solve around my world.  For example, rather than reading a few extra journal articles I need to read, I took a 25 minute break to create a shadowboard (YEAH CLASSIC IE) in my desk drawer using corkboard, a sharpie, and some paperclips.  The main purpose of this endeavor was to keep all my desk stuff from flying all over the place when I shut/open the drawer which drives me crazy.

So, today I solved this problem and am pleased with the result.  Also, on a side note, the white-out is for painting white stuff- not because I make mistakes

Evaluating and Interpreting the Creation of Causal Influence Models

Below (flash required for viewing)  is a poster submission that highlights some of the research I helped to conduct in my first year at UB.  The research objective was to investigate users’ abilities to create Causal Influence Networks, a class of Bayesian networks, with varying complexity and types of relationships, using a causal influence model.  Funding for this research was generously provided by Charles River Analytics.

Abstract: Bayesian networks (BNs) are probabilistic models used to reason under uncertainty by graphically expressing domain knowledge in order to reason about states, causes, and effects. While BNs have many advantages, their complexity can hamper the process of knowledge elicitation and encoding. For example, BNs require the definition of a priori, conditional probabilities: as complex models increase in size, this requires eliciting exponential numbers of complex probabilities. Multiple “canonical modeling” approaches, such as Causal Influence Models (CIMs), have been developed to address these complexities. However, little progress has been made towards human-in-the-loop evaluation of such approaches – specifically, their accessibility and usability, their related user interfaces, and how they enable a user to correctly create and interpret variables and probabilistic relationships. In this study, we evaluated the CIM approach (implemented in a software application) to determine the effect on user task performance. Results indicate that the model complexity has an adverse effect on performance when users are interpreting an existing model; that semantics of a model may impact performance; and that users were generally successful in creating new models of different situations.