人工智能造福人类的那一面（48页）.pdf

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1、AI for Social Good 人工智能造福人类的那一面 Prof.Toby Walsh UNSW Sydney|Data61|TU Berlin 澳大利亚新南威尔士大学教授、AAAI执行委员会成员 From food banks to organ banks Poverty 23 million people in Australia 2.2 million in poverty 11%children 25%pensioners Over 100,000 homeless FoodBank Local Social startup Winners of Microsoft Imagi

2、ne Cup(Australia)Finalists worldwide Using technology To reduce friction for FoodBank Australia(and other NGOs)Collecting&distributing food Fair division To different charities Pickup&delivery problem Induced traveling salesperson problem Online fair divison Goods arrive one by one Agents see items

3、and bid Only 0/1 utilities Special features Online Repeated Combinatorial Storage Expiry dates Unequal entitlements.Like mechanism Agents bid for any item with non-zero utility Item allocated uniformly at random to any bidder Balanced Like mechanism Agents bid for any item with non-zero utility Item

4、 allocated uniformly at random to bidder with fewest items Normative properties THM Like is strategy proof.THM Balanced Like is strategy proof for 2 agents but not for 3.Normative properties THM Both Like and Balanced Like are envy free ex ante THM Balanced Like is envy free up to one item ex post.D

5、eceased organ donation In 1989,average organ was 32 years old.In 2014,average organ was 46 years old.Fair division of organs Online Blood types Age groups Geographical regions.Blood types Supply tracks population Demand different Blood type B at disadvantage No help that O are universal donors Organ

6、&patient quality Kidney Donor Profile Index(KDPI)age of donor,.Expected Post Transplant Survival(EPTS)age of patient,.BOX mechanism Lexicographical preferences Blood/tissue type KDPI and EPTS Time on waiting list,.If KDPImax then 0,exit If KDPI=50 and EPTSEPTS-50 then+3000000,goto 2 If EPTS-50=KDPI=