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Keynote Presentation: Integrating Humans with Software and Systems: Technical Challenges and a Research Agenda Dr. Azad M. Madni [email protected]

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Page 1: Keynote Presentation: Humans with and Systems · Keynote Presentation: Integrating Humans with Software and Systems: Technical Challenges and a Research Agenda Dr. Azad M. Madni

Keynote Presentation:Integrating Humans with Software and Systems: 

Technical Challenges and a Research Agendag

Dr. Azad M. Madni

[email protected]

Page 2: Keynote Presentation: Humans with and Systems · Keynote Presentation: Integrating Humans with Software and Systems: Technical Challenges and a Research Agenda Dr. Azad M. Madni

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Page 3: Keynote Presentation: Humans with and Systems · Keynote Presentation: Integrating Humans with Software and Systems: Technical Challenges and a Research Agenda Dr. Azad M. Madni

Information is not a scarce resource Attention isInformation is not a scarce resource. Attention is.‐ Herbert Simon, 1991

Madni/2Copyright © 2009‐2010  Azad M. Madni

Page 4: Keynote Presentation: Humans with and Systems · Keynote Presentation: Integrating Humans with Software and Systems: Technical Challenges and a Research Agenda Dr. Azad M. Madni

Presentation Outline

System TrendsSystem TrendsOperational ContextEvolving Human RolesgHuman LimitationsExemplar HSI ProblemsHSI PrinciplesFuture HSI ResearchSummary

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Page 5: Keynote Presentation: Humans with and Systems · Keynote Presentation: Integrating Humans with Software and Systems: Technical Challenges and a Research Agenda Dr. Azad M. Madni

System Trends

Increasing size and complexityIncreasing size and complexity

Increasing need for flexible capabilities that can be adapted in operational environmentp

Continuing use of legacy components/subsystems

Demand for rapid fieldingDemand for rapid fielding

These trends are e panding theThese trends are expanding therole of humans in systems.

Madni/4Copyright © 2009‐2010  Azad M. Madni

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Operational Context

Unpredictable dynamic p yenvironment

Kinetic and non‐kinetic operations

Rapidly evolving asymmetric threats  

Need for adaptive response

Need for ongoing tradeoffs

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Evolving Human Roles

From that of an operator outside the system to that of an agentthe system to that of an agentwithin the system 

decision makerdecision maker supervisor with override authority re‐assignable participant (peer, assistant)

These human roles pose new challenges to human systems integration.

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Human‐Systems Integration

A multidisciplinary fieldspans manpower, personnel, training, human factors engineering, system safety, personnel survivability, health hazards, and habitabilityhazards, and habitability

A comprehensive management and technical strategy – to achieve robust human‐system performance in dynamic, y p y ,uncertain operational environments

The key is to capitalize on the strengths of humans, software,and systems  while circumventing their limitations.

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Systems Engineering Mindset

Humans are suboptimal job performers that need to be shored up and compensated forshored up and compensated for

This mindset fails to capitalize on human ingenuity and creativitycreativity 

It leads to inherently incompatible systems relative to human conceptualization of workp

The resulting mismatch inevitability creates human reliability issues that show up as human errorp

Human systems integration strategies need to capitalize on human ingenuity and creativity while circumventing human limitations.

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Human Limitations 

Multitasking / Context switchingMultitasking / Context switching 

Rare event monitoring

Rapid adaptation 

Cognitive overload

Attentional capacity saturation

Decision making under stressg

Risk Homeostasis

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Multitasking Findings

Experiments conducted at Stanford Universitycompared high multitaskers to low multitaskerscompared high multitaskers to low multitaskers

Research Questionscan high multitaskers filter information as well as low multitaskers?do high multitaskers have better memory recall ?do high multitaskers have better memory recall ?do high multitaskers context switch faster ?

Findings high multitaskers had great difficulty filtering out irrelevant information high multitaskers had great difficulty filtering out irrelevant information (prone to distractions)high multitaskers had greater difficulty recalling (couldn’t compartmentalize)high multitaskers had great difficulty context switching (couldn’t separatehigh multitaskers had great difficulty context switching (couldn t separate contexts)

Sometimes can accomplish more by doing less.

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p y g

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Multitasking is the art of g fdistracting yourself from things you’d rather not be doing by doing thembe doing by doing them simultaneously.

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Context Switching

Occurs when humans are interrupted during task performanceInterruptions during tasks that req ire high le el of co ce tratiorequire high level of concentration can prove quite costly

up to 15 minutes to restore same up to 5 utes to esto e sa econcentration levels afterwards

Need to minimize context switching through selective task automation and by limiting sources of interruption.

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y g f p

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Rare Event Monitoring

When monitoring low probability high consequence events, human vigilance tends to drop (Yerkes‐Dobson Law)Dobson Law)

This can frequently cause humans to miss their occurrence producing p gdire consequences

Such tasks are best left to automation and alerting mechanisms.

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Rapid Adaptation

Adaptivity is a unique human capability that is neither absolute or perfecthumans do adapt BUT not quicklyhumans do adapt, BUT… not quicklyit is imperative that scope of adaptation be narrow

System decomposition can achieve narrow adaptation goals

Rate at which humans adapt varies with type of change (e.g., information channels, language, C2 patterns, architectural configurations)

Satisfying human adaptivity needs can give rise to human reliability issuesSatisfying human adaptivity needs can give rise to human reliability issuestradeoff between adaptation rate and human error likelihood and rateneed to define what is acceptable error rate

Need to be mindful of tolerable errorrates when attempting to increase performance  through adaptivity. 

Madni/14Copyright © 2009‐2010  Azad M. Madni

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Cognitive Overload

Humans have cognitive limitationsli it d ki it f t i / i l tilimited working memory capacity for storing/manipulating informationhuman reasoning biased toward using stored knowledge and g g gpatterns

Under sustained cognitive overloadhumans tend to adapt their cognitive strategy (e.g., sacrifice performance on secondary task; shed tasks)

Decision aiding can help with offloading humans as well as prioritizing tasks based on context.

Madni/15Copyright © 2009‐2010  Azad M. Madni

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Attentional Capacity Saturation

When attentional demands exceed human attentional resources, f i it bl ff ( i d t ti t )performance inevitably suffers (e.g., miss detecting events)

The clinical Model of Attention (i.e., focused, sustained, selective, alternating divided attention) is helpful in evaluating attentionalalternating, divided attention) is helpful in evaluating attentional demands

Kahneman’s Attention Theory is especially relevanty p ylevel of arousal determines attentional capacity of humansallocation policy takes into account stable demands and momentary intentionsintentions

Need to maintain near­optimal level of arousal to ensure maximum availability of attentional resources.

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y f

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Decision Making Under Stress

Humans required to deal with large number of factors in short time frameframe

Iran Air Flight 655 shot down by U.S. Navy cruiser Vincennes over the Persian Gulf – incident attributed to stress and ambiguity during d kdecision making Stress can produce “tunnel vision” and impair decision makingI t ti l j d t i t l i d b tInterestingly, judgment is not always compromised by stressUnder stress, humans tend to adopt a simpler mode of information processing that potentially helps with focusing on critical issuesp g p y p g

Humans need training and decision aiding to ensure consideration of all factors and expansion of the available option space.

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Risk Homeostasis

Humans exhibit a target level of riskT t l l f i k i d fi d “th le el of risk a person Target level of risk is defined as “the level of risk a person chooses to accept to maximize the overall expected benefit from an activity.”Wilde (1998) defines risk homeostasis as:“… the degree of risk‐taking behavior and the magnitude of loss, due to accident and lifestyle‐dependent disease beingdue to accident and lifestyle dependent disease, being maintained over time unless there is a change in the target level of risk.”

Risk homeostasis can be overcome through rewarding safety and increasing cost of accidents to the person at fault.

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Exemplar HSI ProblemsExemplar HSI Problems

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Exemplar HSI Problems

Airline Crew Interruptionp

Munich Taxicab study

B iti h C l bi A ti D k D i i C iBritish Columbia Anti‐Drunk Driving Campaign

Metrolink Train Crash

Automobile Blind Side Indicator

Madni/20Copyright © 2009‐2010  Azad M. Madni

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Airline Crew Interruption

Northwest Airline crew was preparing to fly out of DetroitCrew began pre flight checklist but were interrupted by air trafficCrew began pre‐flight checklist, but were interrupted by air traffic controller with new taxiing instructions and warning about wind shearAfter the crew finished talking to the controller, they did not resume going through checklistthrough checklistThey took off without checking status of aircraft’s flaps A flight emergency occurred shortly after takeoff because flaps were in g g y y pwrong positionCrew mistakenly interpreted the problem as wind shear and crashed the plane (NTSB 1988)p ( )

Crew failed to resume going through checklist post­interruptions.

Madni/21Copyright © 2009‐2010  Azad M. Madni

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Munich Taxicab Study

Half the taxicab fleet was equipped with antilock breaking system (ABS); the th h lf h d ld b k tother half had older brake systems

ABS‐equipped drivers started taking more risksThis behavior left their “target risk level” unchangedNon‐ABS drivers drove the same way as before

Accident rate with and without ABS was the same – risk homeostasis.

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British Columbia Anti‐Drunk Driving Campaigng p g

Government campaign in the late 1970’sR d d id t t i t d ithReduced accident rate associated with DUI by nearly 18% over a 4‐month period

d d b hHowever, accidents caused by other factors increased 19% during the same period; why?People started taking more risks on the road leaving “target risk levels” unchanged

Reduction in DUI­related accidents saw a corresponding increase in accidents due to other factors – risk homeostasis.

Madni/23Copyright © 2009‐2010  Azad M. Madni

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MetroLink Train Crash

MetroLink train crashed into Union Pacific freight locomotive … ran four lights

Sanchez, the engineer (driver), didn’t hit brakes before the L.A. train crash, g ( ),

Teenager reported receiving a text message from Sanchez a minute before collision

Explanations offered:i (d i ) di t t d hil t ti (h )‒ engineer (driver) was distracted while texting (human error)

‒ engineer was in the midst of an 11 ½ hour split shift when he ran the first red light (fatigue) ‒ radio communication breakdown between engineer and conductor (comm disruption) ‒ engineer suddenly stricken ill (health issue)‒ engineer suddenly stricken ill (health issue)‒ sun glare may have obscured engineer’s view of signals (environment factor)

Main Reasons:system was not designed for integration with human (assumed a perfect human)system was not designed for integration with human (assumed a perfect human)Sanchez was doing a split shift (tired); also multi‐tasking ‐ ‐ ‐ he was error‐prone

Both systemic design flaws and human error responsible for crash.

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Both systemic design flaws and human error responsible for crash.

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Blind Side Indicator

A decade ago, a blind side indicator was developed for carsdeveloped for cars It was designed to tell if someone was in the driver’s blind sideThis device was never approved, allowed, “put into play;” why?‒ behavioral research predicted that, people were going to over‐use the indicator, and not bother looking over their shoulder … an undesirable change in behavior

Indiscriminate introduction of new technology can potentially change human behavior, and not necessarily for the better.

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HSI Principles

Ensure manageable task‐related cognitive load h d h d f h hEnsure that systems do not have to adapt faster than humans 

can Minimize incidence of frequent context switching and multi­q gtasking through proper task assignment and design of task flow, and selective/partial task automation Maintain human system interaction at a level that keeps humanMaintain human­system interaction at a level that keeps human sufficiently engaged without being cognitively overwhelmedEnsure consistent, predictable system responseMake systems inspectable so humans are not forced to make assumptions (often erroneous) about system state

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Future HSI Research

SE Life Cycle

HSI

…an

Rol

es Hum

aHSI Considerations

ng H

uma n Lim

itati

Dynamic System Adaptation Contexts

Evo

lvi ions

HSI methods need to address human limitations, evolving human roles, dynamic system adaptation contexts, and the full SE life cycle.

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Research Questions

What are the circumstances in which humans are able to adapt readily, slowly, or not at all?How does stress affect human’s ability to assimilate and apply new information?and apply new information?How does sustained cognitive overload modify human behavior and performance?pWhat are the different aspects of humans that need to be addressed in HSI?Where and how should HSI considerations be addressed in the system/software life cycle?

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Research Questions (cont’d)

What system problems can be addressed through appropriate HSI strategies?appropriate HSI strategies?How should research findings in human performance (e.g., adaptivity, decision making under stress, ….) be reflected in HSI strategies?What are the architectural implications of incorporating humans in different capacities within complex systems?humans in different capacities within complex systems?How can HSI strategies inform and guide the development of flexible automation for adaptable systems?How can understanding of human cognitive strategies be used to design decision aiding and performance support systems? 

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y

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Recommendations

Consolidate findings from currently fragmented research findings in human performance within aresearch findings in human performance within a human performance knowledge baseTransform findings into HSI guidelines for developing adaptive/adaptable systemsdeveloping adaptive/adaptable systemsDevelop methods, processes, and tools that incorporate HSI guidelines Introduce HSI methods, processes, and tools to systems and software engineering communities in a manner that clearly conveys their value propositiony y p p

Integrating findings from the fragmented human performance research base is a prerequisite to achieving robust human­system performance.

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Summary 

Systems continue to grow in size and complexitySystems designed for long­lived operation need to beSystems designed for long lived operation need to be able to adapt to changing/emerging operational needs

continually changing threats and environmental factorsevolving human roles

System adaptivity is upper‐bounded by tolerable human error rate

For robust human‐system performanceneed for human to multitask and context switch needs to be minimizedautomation should be used to monitor and flag rare events and aggregate informationhuman cognitive strategies under overload condition needs to be understood for effective d i f d i i idi d f t tdesign of decision aiding and performance support systems

Human‐system integration considerations should be brought to bear early and throughout the systems engineering life cycle

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Page 33: Keynote Presentation: Humans with and Systems · Keynote Presentation: Integrating Humans with Software and Systems: Technical Challenges and a Research Agenda Dr. Azad M. Madni

References

Madni, A.M. “Integrating Humans with Software and Systems: Technical Challenges and a Research Agenda” INCOSE Journal ofTechnical Challenges and a Research Agenda,  INCOSE Journal of Systems Engineering, Vol. 13, No. 3, 2010. Kahneman, D.  Attention and Effort, Englewood Cliffs, N.J. , P ti H ll 1973Prentice‐Hall, 1973. Wilde, G.J.S.  Risk Homeostasis Theory: An Overview, Injury Prevention Journal, 1998, Vol. 4, Issue 2, pp. 89‐91.  J ppHammond, K.R.  Judgments Under Stress, Oxford University Press, Inc., New York, New York 2000.O hi E N C dW A D “C i i C l i M diOphir, E., Nass, C. and Wagner, A.D.  “Cognitive Control in Media Multitaskers,” PNAS, Vol. 106, No. 37, pp. 15583‐15587, September 15, 2009.

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