The Human Feedback Loop - World Usability Day 2012
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The document discusses the human feedback loop in computing. It defines the feedback loop as processes that evaluate, moderate, and confirm as information passes from the human through an interface to a computer and back. It outlines four stages: 1) evidence of a behavior is measured and stored, 2) relevant information is relayed to the human, 3) the information illuminates paths ahead, and 4) the human recalibrates behavior and acts, restarting the loop. The document discusses why feedback loops are important for understanding reality and tapping into human learning and aspirations. It also notes challenges in designing effective feedback loops and potential future applications.
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The Human Feedback Loop - World Usability Day 2012
- 1. The Human Feedback Loop in Computing Panel Discussion World Usability Day November 08, 2012 LexisNexis Dayton
- 3. Vishal Saboo & Dan Mecher, Hobsons Learning, Education, Information-seeking Vishal Saboo is a Product Manager at Hobsons who cares deeply about user experience and customer service. Prior to Hobsons, he worked for 10 years as a Director of Consulting at Definitive Solutions and also as a Systems Analyst at Infosys. He loves sports photography, travel, music and his family. Dan Mecher has over 10 years of experience in various design disciplines including creative, interactive, print, web site, web application and mobile. In his current role at Hobsons, his focus has shifted toward user experience and user research, combining aspects of design and human behavior. Hobsons is dedicated to helping students progress successfully through each stage of the learning lifecycle. We develop software for education that allows students to create personalized academic and career plans…
- 4. Phil Wittmer, LexisNexis Fitness and Exercise Phil Wittmer is a Senior Idea Designer with Customer Discovery and Innovation. He works with business stakeholders to cultivate and develop product ideas, test those ideas with customers, and then send the best ones to product development. Phil has worked at LexisNexis for 9 years. Before his current role, Phil worked at The Oxford Associates and Reynolds & Reynolds as a Technical Writer and Business Analyst.
- 5. Chris Hamant, Elsevier Self-actualization Chris is a graduate of Wright State University with a bachelor's degree in Computer Science. He currently works at Elsevier in the User Centered Design group supporting development needs, producing prototypes and various other tasks. Like most humans, his interests are pretty varied and wide ranging… probably too much to fit within the confines of a slide deck with a one-liner. He does have more than a passing interest in the various cultures and sub-cultures within the burgeoning 'Quantified Self' community and hopes to learn how it can help him be more effective in everything he does.
- 6. Jacob Myers, LexisNexis Gaming Graduate of Wright State University with a Masters in Computer Science, and has worked 5 years at LexisNexis in software development. The last 3 years have been in the iLabs research group working in a multitude of varying spaces from visualization to text classification. Currently heavily focused on text analytics work, involving classification technologies and search engines; primarily in the HPCC environment. Specialties include software design, system administration, electrical engineering, and playing too many video games. Incapable of resisting a puzzle.
- 7. Moderator: Rich Miller, LexisNexis Sports Psychology & Coaching Research Scientist in the LexisNexis R&D group for 12 years. Previously served in UI-related roles at AT&T, LexisNexis, and SDRC. Focuses on new technology and approaches related to UI/UX, e.g. analytics/visualization, mobile computing, information capture, UI design, and product strategy. Rich has a Ph.D. in Experimental Psychology from Miami University. In his non-work life, Rich enjoys playing and coaching basketball, and following sports, music, and film.
- 8. The Human Feedback Loop in Computing • Definition/Context • • Loops through the interface that evaluate, moderate, and confirm processes as they pass from the human through the interface to the computer and back (Wikipedia HCI entry) Our focus is on how to use the feedback loop to design better interfaces… • WIRED article >>
- 9. 4 Stages of the HFL 1. 2. 3. 4. Evidence - A behavior must be measured, captured, and stored. Relevance - info relayed to human - not in the rawdata form in which it was captured but in a context that makes it emotionally resonant. Consequence - information must illuminate one or more paths ahead. Action - human recalibrates a behavior, makes a choice, and acts…action is measured, and the feedback loop keeps going
- 10. Background and History • 18th century – steam engine design • 1940s – Norbert Wiener and cybernetics • 1960s - Albert Bandura – Providing individuals a clear goal and a means to evaluate their progress toward that goal greatly increased the likelihood that they would achieve it. – Self-efficacy = the more we believe we can meet a goal, the more likely we will do so. – Since Bandura’s work, feedback loops have been thoroughly researched and validated in psychology, epidemiology, military strategy, environmental studies, engineering, and economics. – Feedback loops are a common tool in athletic training plans, executive coaching strategies, and a multitude of other self-improvement programs (though some are more true to the science than others).
- 11. Why are feedback loops so hot now? • Tech drivers – Faster computers/networks and cheap storage – More, cheaper sensors and automation of data capture • accelerometers (which measure motion), GPS sensors (which track location), and inductance sensors (which measure electric current). – Capabilities and preponderance of devices that can measure things – Explosion of apps – Central to the emerging Natural UI (NUI) model of design (e.g. Kinect) • Human behavior drivers – Better methods and approaches • e.g. Ambient Devices creates energy savings by using “preattentive processing” to achieve a feedback sweet spot (between too passive and too intrusive), where the information is delivered unobtrusively but noticeably. – Bottom-up feedback loops have supplemented big-brother top-down practices – Discovery of self-help power within personalized devices – Personalized data much more available and demanded
- 12. Why are HFLs important? • “The intransigence of human behavior has emerged as the root of most of the world’s biggest challenges.” – Intransigence leads to many undesirable but avoidable things such as obesity, smoking, chronic illnesses, pollution from personal energy consumption, etc. • They provide previously missing pieces of info used to understand reality – One can go years without really knowing how to improve something if you are never told or think much about the results of your actions – Previously impossible behavior and outcomes may now be possible • Feedback taps into something core to the human experience, even to our biological origins. – “People are proactive, aspiring organisms.” Feedback taps into those aspirations. – Feedback loops are how we learn, whether we call it trial and error or course correction.
- 13. HFL landscape: work/play X latency
- 14. Kinect FBloop overlayed onto real-world activity
- 15. FeedForward • A method of teaching and learning that… indicates a desired future behavior or path to a goal (Wikipedia) – Provides information, images, etc. exclusively about what one could do right in the future…focuses on learning in the future – Info provided is about anticipated events (what’s coming), not effects of behavior on past events or success • Examples – Tablet help for gesture-language learning – Nba baller beats • See upcoming skill moves you will need to execute – Sports simulations as prep for actual games • e.g. Madden football, NBA2K basketball – Pre-race course run-throughs for runners
- 16. Discussion questions 1. For the area that you are representing, please describe example(s) of the human feedback loop in action. – Which HFLs in UI design have been the most effective? – Under what conditions do they work best/least? – ?Group activity: audience places sticky notes on 2D landscape poster 2. What are the design challenges for leveraging and incorporating feedback loops? 3. How can feedforward be used in UI design? 4. What are potential applications that we have not yet seen?
- 17. 1 2&3 4
Notas do Editor
- A once habitually traditional behaviorist, Bandura came up with his own spin on things by introducing children to bobo dolls – inflatable pear shaped balloons, weighted at the bottom to induce them to bounce back when hit. Specifically, the children were introduced to the dolls after first watching adults hit, scream at, and kick them. The children surprised no one by then punishing the dolls exactly as the adults had, though they’d been given no instructions to do so. The fact that the children changed their behavior without rewards suggested the major implication of this study: observation alone can change behavior, and significantly affect learning. In many cases observation is the most effective mode of learning, with one obvious example being the enormous impact of peer influence. Many recent theorists believe we are evolutionarily primed to learn through observation. Bandura developed social learning theory in response to this and similar work. Social learning theory emphasizes that 1) people can learn by observing; 2) specific learning may or may not be associated with an accompanying behavioral change; 3) cognition plays a critical role in learning. Observation is better at teaching some things, such as morality and aggression, and not as good at teaching other things, such as calculus and physics. With whatever is being taught, modeling can be one of the most effective components. Here’s some good info on social learning theory, and here’s a good link on Bandura.
- Feedforward, Behavior and Cognitive Science is a method of teaching and learning that illustrates or indicates a desired future behavior or path to a goal.[1] Feedforward provides information, images, etc. exclusively about what one could do right in the future, often in contrast to what one has done in the past. The feedforward method of teaching and learning is in contrast to feedback concerninghuman behavior because it focuses on learning in the future, whereas feedback uses information from a past event to provide reflection and the basis for behaving and thinking differently. In isolation, feedback is the least effective form of instruction, according to US Department of Defense studies in the 1980s. Feedforward is the opposite of feedback, and was coined by Peter W. Dowrick in his dissertation.[2]One concept of feedforward originated in behavioral science. Related concepts have emerged in biology, cybernetics, and management sciences (see separate entries in Wikipedia). Since the 1970s, the understanding of feedforward has evolved to become more explicit, more useful, and to help the understanding of brain function and rapid learning. The concept contributed significantly to research and development of video self modeling (VSM). The most productive advances in feedforward came from its association with videos that showed adaptive behavior one had never exhibited before, at least not in the context shown in the video (see Dowrick, 1983, pp. 111, 121; 1991, pp. 110–3, 120-2, 240-1; 1999, esp. pp. 25–26).[3][4] For example, a boy with autism role-plays squeezing a ball (stress management technique) instead of having a tantrum when his work is found imperfect by the teacher – or a selectively mute child is seen on video talking at school (which she never did), by editing in footage of her talking at home (location disguised by use of a classroom backdrop). By selectively editing a video, a clip was made that demonstrated the desired behavior and allowed the children to learn from their future successes.By reference to its historical context of VSM, it became recognized that feedforward comprised component behaviors already in therepertoire, and that it could exist in forms other than videos. In fact, feedforward exists as images in the brain, and VSM is just one of many ways to create these simulations. The videos are very short – the best are 1 or 2 minutes long, and achieve changes in behavior very rapidly. Under the right conditions, a very few viewings of these videos can produce skill acquisitions or changes in performance that typically take months and have been resistant to change by other methods. The boy with autism and the girl with selective mutism, mentioned above, are good examples. Further examples can be found in journal articles,[5][6][7] and on the web (e.g., in sport,http://keithlyons.wordpress.com/2009/06/28/feedforward/).The evidence for ultra-rapid learning, built from component behaviors that are reconfigured to appear as new skills, indicates the feedforward self model mechanism existing in the brain to control our future behavior [8] See Figure 1. [insert Fgure 1 about here]. That is, if the conditions of learning are right, the brain takes pieces of existing skills, puts them together in new ways or in a different context, to produce a future image and a future response. Thus we learn from the future – more rapidly than we learn from the past. Further evidence comes from cognitive processes dubbed “mental time travel” [9] and for parts of the hippocampus etc. where they occur.[10]However, the links between these hot spots in the brain and feedforward learning have yet to be confirmed.Feedforward concepts have now become firmly established in at least four areas of science, and they continue to spread. Feedforward often works in concert with feedback loops for guidance systems in cybernetics or self-control in biology (**insert link). Feedforward in management science enables the prediction and control of organizational behavior.[11] These concepts have developed during and since the 1990s. Feedforward in procedures of behavior change and rapid learning have been quietly with us since the mid 1970s. In summary, feedforward in behavioral and cognitive science may be defined as “images of adaptive future behavior, hitherto not mastered”; images capable of triggering that behavior in a challenging context. Feedforward is created by restructuring current component behaviors into what appears to be a new skill or level of performance.