Wiser  

On  Improving  Decisions    

Cass  R.  Sunstein  Harvard  Law  School  

Today’s  Talk:  Group  Error  and  Group  Success  

•  1)  Key  lessons  from  behavioral  science:  How  individuals  go  wrong        

•  2)  Recent  findings  about  how  groups  (including    company  boards)  go  wrong,  so  we  have  a  

•  New  claim:  linking  behavioral  insights  about  individual  errors  to  special  group-­‐level  and  challenges    

•  Empirical  note  on  boards  in  highest-­‐performing  companies  (“a  good  fight  now  and  then”);  investment  clubs  

•  3)  How  groups  can  do  beQer    

Three  Separate  Problems  for  Groups  

•  1)  NOISE:  Different  groups  make  different  decisions  on  the  same  topics/issues/applicaXons,  for  no  good  reason.  (Decisions  made  right  aYer  lunch?  Right  aYer  three  posiXve  outcomes?  By  different  people?)  

•  2)  BIAS:  Behavioral  biases,  eg  status  quo  bias  (Chicago  story);  favoriXsm,  good-­‐faith  personal  inclinaXons,  good-­‐faith  biases    

•  3)  INSUFFICIENT  INFORMATION:  one  person,  or  a  few,  end  up  dominaXng;  some  people  self-­‐silence;  premature  consensus  

•  Results  of  these  problems?  Errors!  

A  Glimpse,  1:  Anxious  Leaders  

A  Glimpse,  2:  Quiet  Leaders?    

A  Glimpse,  3:  Discord  and  InnovaXon  (Consensus  can  be  sXfling  and  overrated)  

The  Behavioral  RevoluXon  

For  Example:  

Another  Example  

•  You  have  a  serious  illness  and  you  are  considering  an  operaXon.  You  are  told  that  of  the  people  who  have  that  operaXon,  90  percent  are  alive  aYer  ten  years.  Do  you  have  it?  

•  You  have  a  serious  illness  and  you  are  considering  an  operaXon.  You  are  told  that  of  the  people  who  have  that  operaXon,  10  percent  are  dead  aYer  ten  years.  Do  you  have  it?  

Behavioral  Challenges  

•  Behavioral  science  has  idenXfied  a  series  of  individual-­‐level  mistakes.  For  example:  

•  1)  Planning  fallacy  (tasks  take  longer  than  you  think!)  

•  2)  Availability  bias  (emphasizing  parXcular  or  recent  events,  compare  ebola)  

•  3)  OpXmism  bias  (80  percent  of  drivers  think  they  are  beQer  than  the  average  driver;  lawyers  too;  others  too)  

More  Challenges  •  4)  Self-­‐serving  bias  (thinking  one’s  own  side  is  likely  to  be  right  and  likely  to  win)  

•  5)  Loss  aversion  (golfers  and  teachers;  relevant  to  negoXaXons)  

•  6)  Anchoring  (relevant  to  economic  decisions  and  negoXaXons)’  

•  7)  Overconfidence  (maybe  THE  MOST  IMPORTANT)  

•  8)  Status  quo  bias  (the  tale  of  Intel)  •  9)  Salience  

Group  Errors  

•  General  finding:  Group  decisions  increase  confidence  and  decrease  variance  without  increasing  accuracy.    

•  ExcepXon:  “eureka”  problems.  This  is  important  and  intriguing.  It  suggests  a  possible  response  to  all  three  problems.    

•  BUT:  Groups  get  unified,  confident,  and  oYen  wrong  (unless  they  take  steps  to  prevent  that!)  

An  Example:  the  Colorado  Study  

•  Boulder  •  Colorado  Springs  •  Climate  change,  affirmaXve  acXon,  same-­‐sex  unions  

•  What  happened?  •  In  groups;  and  in  anonymous,  private  views  

Another  Example:  The  Risky  ShiY  

•  Americans  and  risk  •  But:  Taiwanese  and  risk  •  Synthesis:  Group  polarizaXon  

Findings:  Individuals  vs.  Groups  

•  Fact:  The  planning  fallacy  gets  WORSE  at  the  group  level  

•  Fact:  InformaEonal  pressures  lead  people  to  stay  quiet  (“the  senior  employees  must  be  right”  or  “the  famous  scienXsts  must  be  right”)  

•  Fact:  ReputaEonal  pressures  lead  people  to  stay  quiet  (eg  younger  or  newer  employers  in  a  firm)  

A  Pervasive  Problem  

•  First  finding:  firms  and  groups  oHen  amplify,  and  do  not  aIenuate,  the  various  biases  

•  So  groups  do  even  worse  than  individuals  

Challenges,  conXnued  

•  Second  finding:  Hidden  profiles  and  common  knowledge    

•  Note  on  “cogniXvely  central”  people  vs.  “cogniXvely  peripheral”  people  

•  Third  finding:  Group-­‐level  cascades  (music  download  study)  

•  InformaEonal  factors  contribute,  and  reputaEonal  factors  contribute  

The  Future?  

•  The  problem  of  “noise”  or  random  variability:  the  fact  that  different  people  in  the  same  situaXon  make  very  different  judgments.  

•  One  view  (Kahneman):  “Noise  is  costly  to  organisaXons,  which  are  essenXally  factories  for  making  decisions.”  

•  Another  view:  overconfidence  and  failure  to  elicit  informaXon  is  the  most  serious  problem  for  corporate  boards  

 SoluXons?  EliciXng  InformaXon  and  Reducing  Bias  •  The  task:  to  elicit  informaXon  that  people  have  (cf.  hidden  profiles  and  their  destrucXve  effects).  

•  Simple  idea:  make  sure  diverse  people  feel  VERY  free  to  talk  (for  leaders:  silence  is  golden)  

•  Simple  idea:  reduce  informaXonal  and  reputaXonal  pressure    

•  “EquiXes”  and  the  federal  government  

Two  Tales  

Not  Ideal  (and  the  Curse  of  Happy  Talk)  

SoluXons?    EliciXng  InformaXon,  Reducing  Noise  

and  Bias      •  Role  assignment  vs.  hidden  profiles  (cf.  federal  government  in  the  US  and  when  it  works)  

•  Red  teams  (not  devil’s  advocates)  •  The  role  of  leadership  (important  for  leaders  to  be  quiet  at  first,  to  reduce  self-­‐silencing)  

•  Look  who’s  talking?  

SoluXons?  CounteracXng  Noise  AND  Bias  

•  IdenXficaXon  vs.  selecXon  •  Noise  detecXon  machinery?  •  “JurisdicXon  creep”  vs.  “capture,”  and  the  federal  government  

SoluXons?  Factor  C  

 •  General  intelligence  is  a  predictor  of  contribuXon  to  group  performance,  and  a  good  one  

•  But  “factor  c”  is  an  even  beQer  predictor  (the  MIT  study);  what  is  it?  

Factor  C  

•  First:  social  percepXon  (the  reading  the  eyes  in  the  mind  test)  

•  Second:  how  many  people  contribute?  •  Third:  how  many  women?  •  These  factors,  taken  together,  were  more  predicXve  of  performance  than  general  intelligence    

•  The  importance  of  certain  norms  

Conclusions  

•  In  last  forty  years,  we  have  learned  a  great  deal  about  individual-­‐level  mistakes.  They  are  systemaXc  and  idenXfiable.  

•  They  are  not  eliminated  at  the  group  level.  OYen  they  get  worse.  

•  General  intelligence  helps;  factor  c  helps  even  more.  

A  Final  Conclusion  

•  The  best  path  forward  the  creaXon  of  a  certain  kind  of  firm  or  group-­‐level  culture,  one  that  systemaXcally  counteracts  the  underlying  risks.  

•  What’s  a  team  player?  •  The  disXncXve  role  of  leaders  and  presenters