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The	
  human	
  use	
  of	
  human	
  beings	
  
Naviga1ng	
  a	
  world	
  beyond	
  employment	
  
By	
  George	
  Zarka...
The	
  end	
  of	
  work?	
  
The	
  fear	
  is	
  old	
  
June	
  29,	
  1955,	
  	
  
Punch	
  Magazine.	
  
The	
  story	
  so	
  far	
  
AI	
  (1960s)	
  
AI	
  (1990s)	
  
AI	
  (Now)	
  
ENIAC	
  (1946)	
  
The	
  AI	
  “Winter...
State	
  of	
  play	
  Cogni1ve	
  Automa1on	
  
Time	
  
Now	
  
Recogni+on	
  intelligence	
  
	
  
Cogni+ve	
  Intellig...
Enablers	
  of	
  work	
  automa1on	
  
Robo+c	
  Process	
  
Automa+on	
  
	
  
	
  
	
  
	
  
	
  
Cogni+ve	
  
automa+o...
Scalability:	
  AI	
  as	
  a	
  pla`orm	
  
AI	
  interfaces	
  
(Natural	
  language	
  conversa1ons)	
  
Machine	
  Lea...
The	
  automa1on	
  of	
  jobs	
  
Source:	
  The	
  Future	
  of	
  Employment,	
  by	
  C.	
  Frey	
  and	
  M.	
  Osbor...
Source:	
  McKinsey	
  Interim	
  report	
  on	
  
automa1on	
  of	
  jobs,	
  Nov.	
  2015	
  
45%	
  	
  
of	
  job	
  a...
Country	
  and	
  educa1on	
  level	
  variability	
  
9%	
  	
  
of	
  jobs	
  will	
  be	
  
fully-­‐automated	
  
Sourc...
Automa1ng	
  the	
  marke1ng	
  analyst	
  
Source:	
  WTW	
  Research,	
  March	
  2016	
  
$20,000	
  
$123,000	
  
Previous	
  impacts:	
  Automa1on	
  means	
  less	
  work…	
  
…	
  but	
  not	
  
less	
  jobs	
  
50%	
  increase	
  in...
Automa1on	
  =	
  higher	
  produc1vity…	
  
…flaoening	
  out	
  around	
  the	
  end	
  of	
  ‘00s	
  
Source:	
  Wells	
  Fargo	
  
The	
  big	
  slowdown:	
  Not	
  enough	
  automa1on?	
  
Source:	
  Boston	
  Consul1ng	
  Group	
  
Manufacturing	
  costs	
  are	
  on	
  the	
  rise…	
  
The	
  rising	
  cost	
  of	
  “cheap”	
  labour	
  
The	
  decreasing	
  cost	
  of	
  robots	
  
The	
  Solow	
  Paradox	
  
You	
  can	
  see	
  the	
  
computer	
  age	
  
everywhere	
  but	
  in	
  
the	
  produc1vit...
A	
  non-­‐equilibrium	
  perspec1ve	
  
The	
  change	
  is	
  on	
  
2nd	
  Industrial	
  
Revolu+on	
  
	
  
“The	
  assembly	
  
line”	
  
	
  
Features:	
  	
...
The	
  5	
  Forces	
  of	
  Change	
  
Source:	
  CHREATE	
  Consor1um	
  
Social  &  
Organiza.onal  
reconfigura.on
A  tr...
Possible	
  futures	
  
LOW	
  
Democra+za+on	
  of	
  Work	
  
Technological	
   Empowerment	
  
HIGH	
  
HIGH	
  
LOW	
 ...
A	
  shared	
  economy	
  for	
  talent	
  
Company	
  
A	
  
Company	
  
B	
  
Company	
  
C	
  
Company	
  
D	
  
Shared...
Transformed	
  jobs:	
  A	
  more	
  humane	
  doctor	
  
Proficiency	
  role	
  (now)	
   Pivotal	
  role	
  (future)	
  
...
New	
  jobs	
  created	
  
Data,	
  Talent	
  &	
  AI	
  integrator	
   Virtual	
  Culture	
  Architect	
  Robot	
  Traine...
A	
  new	
  cyberne1c	
  rela1onship	
  
Second-­‐order	
  cyberne1cs	
  in	
  the	
  era	
  of	
  
machine	
  intelligenc...
Cyber-­‐physical	
  	
  Systems	
  &	
  Industry	
  4.0	
  
From	
  hierarchies	
  to	
  networks	
  
CPS-­‐based	
  autom...
Zero	
  Latency	
  Enterprise	
  
Company	
  
Organisa1on	
  
Enterprise	
  Systems	
  
Enterprise	
  Applica1ons	
  
Ente...
The	
  Responsive	
  Organisa1on	
  
An	
  agile,	
  client-­‐facing,	
  innova)ve	
  organiza)on	
  that	
  con)nuously	
...
People	
  Networks:	
  reinven1ng	
  business	
  
organisa1on	
  
•  Self-­‐organised	
  ad	
  hoc	
  teams	
  
•  Build-­...
Future-­‐proofing	
  
Transforming	
  business	
  with	
  work	
  automa1on	
  
Source:	
  “Lead	
  the	
  Work”	
  by	
  R.	
  Jesuthasan,	
  J...
Geyng	
  there:	
  Scaling	
  Agile	
  organisa1on	
  
Apply	
  agile	
  prac1ce	
  across	
  the	
  organisa1on	
  
hop:/...
Geyng	
  there:	
  digital	
  engagement	
  
Apply	
  Next	
  Genera1on	
  
Integrated	
  Digital	
  
Engagement	
  Model	...
Geyng	
  there:	
  machine	
  intelligence	
  for	
  EX	
  
Build	
  the	
  machine	
  intelligence	
  layer	
  of	
  the	...
Thank	
  you	
  
George	
  Zarkadakis,	
  PhD,	
  CEng	
  
@zarkadakis	
  
The impact of AI on work
The impact of AI on work
The impact of AI on work
The impact of AI on work
The impact of AI on work
The impact of AI on work
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The impact of AI on work

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Artificial Intelligence and mobile robotics are transforming businesses and the economy: this deck explores possible futures for companies and workers.

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The impact of AI on work

  1. 1. The  human  use  of  human  beings   Naviga1ng  a  world  beyond  employment   By  George  Zarkadakis,  PhD,  CEng  
  2. 2. The  end  of  work?  
  3. 3. The  fear  is  old   June  29,  1955,     Punch  Magazine.  
  4. 4. The  story  so  far   AI  (1960s)   AI  (1990s)   AI  (Now)   ENIAC  (1946)   The  AI  “Winters”   Lighthill   report,   DARPA   cuts   5th  Gen   fizzle  
  5. 5. State  of  play  Cogni1ve  Automa1on   Time   Now   Recogni+on  intelligence     Cogni+ve  Intelligence     General  Intelligence   (?)  
  6. 6. Enablers  of  work  automa1on   Robo+c  Process   Automa+on             Cogni+ve   automa+on   Social  Robo+cs                           TASKS   Rou1ne,   High-­‐volume   Non-­‐rou1ne,     crea1ve   Rou1ne,    collabora1ve     MATURITY     HIGH     EMERGING     MEDIUM     IMPACT   MEDIUM   HIGH   HIGH  
  7. 7. Scalability:  AI  as  a  pla`orm   AI  interfaces   (Natural  language  conversa1ons)   Machine  Learning  
  8. 8. The  automa1on  of  jobs   Source:  The  Future  of  Employment,  by  C.  Frey  and  M.  Osborne       47%     of  jobs  will  be   fully-­‐ automated  in   the  next  10   years  
  9. 9. Source:  McKinsey  Interim  report  on   automa1on  of  jobs,  Nov.  2015   45%     of  job  ac1vi1es    can     be  automated   +AI  =   58%     of  job  ac1vi1es    can     be  automated   60%     of  jobs  can  have       30%     of  their     ac1vi1es  automated   Hello  Jane,   you  look  great   today!  How   can  I  help   you?   Automa1ng  tasks  (not  jobs)   5%     of  jobs  will  be   fully-­‐automated  
  10. 10. Country  and  educa1on  level  variability   9%     of  jobs  will  be   fully-­‐automated   Source:  Arntz,  M.,  T.  Gregory  and  U.  Zierahn  (2016),  “The  Risk  of  Automa1on  for  Jobs  in   OECD  Countries:  A  Compara1ve  Analysis”,  OECD  Social,  Employment  and  Migra1on  Working   Papers,  No.  189,  OECD  Publishing,  Paris.  
  11. 11. Automa1ng  the  marke1ng  analyst   Source:  WTW  Research,  March  2016   $20,000   $123,000  
  12. 12. Previous  impacts:  Automa1on  means  less  work…   …  but  not   less  jobs   50%  increase  in  total  number  of   employed  people     Wage  rise  2.23%  faster  than   infla1on  
  13. 13. Automa1on  =  higher  produc1vity…   …flaoening  out  around  the  end  of  ‘00s  
  14. 14. Source:  Wells  Fargo   The  big  slowdown:  Not  enough  automa1on?  
  15. 15. Source:  Boston  Consul1ng  Group   Manufacturing  costs  are  on  the  rise…  
  16. 16. The  rising  cost  of  “cheap”  labour  
  17. 17. The  decreasing  cost  of  robots  
  18. 18. The  Solow  Paradox   You  can  see  the   computer  age   everywhere  but  in   the  produc1vity   sta1s1cs.  
  19. 19. A  non-­‐equilibrium  perspec1ve  
  20. 20. The  change  is  on   2nd  Industrial   Revolu+on     “The  assembly   line”     Features:     §  Underpinning  for   Coase’s  theory  of   the  firm   §  Companies  as   social  ins1tu1ons   §  Organiza1on  of   work  into  jobs   §  Jobs  as  careers       3rd  Industrial   Revolu+on     “Nikefica1on”     Features:     §  Technology   enablement  and  the   web     §  Companies  as  the   nexus  of  contracts   §  Streamlining  of  jobs   to  enable  outsourcing             4th  Industrial   Revolu+on     “Uberiza1on”     Features:     §  Mobile,  sensors,  AI  and   machine  learning   §  Companies  as   pla`orms   §  Disaggrega1on  of  work   into  ac1vi1es   §  Talent  on  demand     1900s   1960s-­‐1990s   2000s-­‐  
  21. 21. The  5  Forces  of  Change   Source:  CHREATE  Consor1um   Social  &   Organiza.onal   reconfigura.on A  truly   connected   world All  inclusive,   global  talent   market Human  &   machine   collabora.on Exponen.al   paCern  of   technology   change 1 2 3 4 5 •  Work  Automa.on  (RPA,  CA,  Social  Robo.cs) •  Blockchains •  3D  prin.ng •  IoT Technological  Empowerment •  Short  term •  Agile •  Skills-­‐based •  Networks •  PlaVorms Democra.za.on  of  Work  
  22. 22. Possible  futures   LOW   Democra+za+on  of  Work   Technological   Empowerment   HIGH   HIGH   LOW   Work     Reimagined   “UBER”     Empowered   Current   State   Today     turbo-­‐charged   1 2 34 Source:  CHREATE  Consor1um  
  23. 23. A  shared  economy  for  talent   Company   A   Company   B   Company   C   Company   D   Shared  talent  pla`orm   AI-­‐enabled   IT   HR   CS  
  24. 24. Transformed  jobs:  A  more  humane  doctor   Proficiency  role  (now)   Pivotal  role  (future)   Doctor  Performance   Doctor  Performance   Pa1ent  Sa1sfac1on   Pa1ent  Sa1sfac1on   AI  -­‐  Enabled   As  cogni1ve  automa1on  gets  beoer  with  diagnosis  human  doctors  (a  “proficiency  role”)  can   spend  more  1me  with  pa1ents,  becoming  a  “pivotal  role”  in  healthcare  systems  
  25. 25. New  jobs  created   Data,  Talent  &  AI  integrator   Virtual  Culture  Architect  Robot  Trainer   Cyber  Ecosystem  Designer   AI  Ethics  Evaluator  
  26. 26. A  new  cyberne1c  rela1onship   Second-­‐order  cyberne1cs  in  the  era  of   machine  intelligence     Humans  and  machines  working  together:  machines   managing  complexity,  humans  providing  crea1vity   From  knowing  what  you  do  not  know  and  searching  for  it     …to  …     …not  knowing  what  you  do  not  know  and  having  “someone”  to  help  you  discover  it    
  27. 27. Cyber-­‐physical    Systems  &  Industry  4.0   From  hierarchies  to  networks   CPS-­‐based  automa+on   Field  level   Control  (PLC)  Level   Process  Control  Level   Plant  management   Level   ERP  Level   Automa+on  hierarchy  
  28. 28. Zero  Latency  Enterprise   Company   Organisa1on   Enterprise  Systems   Enterprise  Applica1ons   Enterprise  App  Integra1on   Data  Store                                                           In  a  real  )me,  zero  latency  enterprise,  informa)on  is  delivered  to  the  right  place  at  the  right   )me  for  maximum  business  value.*   *Defini1on  of  ZLE  by  Gartner  
  29. 29. The  Responsive  Organisa1on   An  agile,  client-­‐facing,  innova)ve  organiza)on  that  con)nuously  learns  and  op)mizes  talent   and  technologies  in  order  to  deliver  superior  products  and  services.   Machine   Intelligence   Applica1ons   People   Networks   Business  Systems   Learning  &  Conversa1ons   Business  Applica1ons   Business  App  Integra1on   Virtual  Data  Store  
  30. 30. People  Networks:  reinven1ng  business   organisa1on   •  Self-­‐organised  ad  hoc  teams   •  Build-­‐in  discovery  from  design  to  customer  service   •  Scaling  Agile   •  Cross-­‐market  &  Cross-­‐exper1se   •  Collabora1on  pla`orms   •  AI  enabled  UI/UX   •  Predic1ve  analy1cs  
  31. 31. Future-­‐proofing  
  32. 32. Transforming  business  with  work  automa1on   Source:  “Lead  the  Work”  by  R.  Jesuthasan,  J.  Bourdeau,  D.  Creelman   Assignment   Organisa1on   Rewards   •  Self-­‐contained   •  Unlinked   •  Exclusive   •  Stable   •  Deconstructed  Tasks   •  Dispersed   •  Project-­‐bound   •  Constructed  Jobs   •  Anchored   •  Employment-­‐Bound   •  Long-­‐Term   •  Collec1ve  and   consistent   •  Tradi1onal   •  Permeable   •  Interlinked   •  Collabora1ve   •  Flexible   •  Short-­‐term   •  Individualised  and   Differen1ated   •  Imagina1ve   AI  enabled  
  33. 33. Geyng  there:  Scaling  Agile  organisa1on   Apply  agile  prac1ce  across  the  organisa1on   hop://crowdmics.com/  hop://crowdmics.com/   INNOVATE DELIVER VALIDATE UNDERSTAND
  34. 34. Geyng  there:  digital  engagement   Apply  Next  Genera1on   Integrated  Digital   Engagement  Model  (IDEM)     for    the  digital   transforma1on    of  work   Behavioural   Modelling   Human-­‐ machine   conversa1ons   AI  Interface   Data   Worker   experience   Human-­‐machine   collabora1on  
  35. 35. Geyng  there:  machine  intelligence  for  EX   Build  the  machine  intelligence  layer  of  the  responsive  organisa1on  
  36. 36. Thank  you   George  Zarkadakis,  PhD,  CEng   @zarkadakis  

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