The Social Life of Information

The Social Life of Information Chapter 2 – Agents and Angels William H. Bowers – whb108@psu.edu

Topics • Chatterbots • Eliza & ALICE Meet Shallow Red • Other Agents • The Road Ahead William H. Bowers – whb108@psu.edu

Topics • Ranks of Agents • Information Brokering • Product Brokering • Merchant Brokering • Negotiating • How Autonomous? William H. Bowers – whb108@psu.edu

Topics • The Brightest Fell • Moore Solutions • Fake PayPal Email • Separate Spheres William H. Bowers – whb108@psu.edu

Chatterbots • Parse sentences • Simulates human responses • Autonomous agents • Can help with customer support William H. Bowers – whb108@psu.edu

Chatterbots • Eliza http://www.manifestation.com/neurotoys/eliza.php3 • Shallow Red • Amazon’s personalized suggestions William H. Bowers – whb108@psu.edu

Eliza & ALICE Meet Shallow Red • Eliza: "Hello. I am ELIZA. How can I help you?" • Shallow Red: "Hi there. I hope all goes well. Please ask me some questions.“ • ALICE: "You are very [nice].“ • Shallow Red: "Thanks, that means a lot coming from a real person.“ • ALICE: "It was my pleasure.“ • Eliza: "Why do you say your pleasure?“ William H. Bowers – whb108@psu.edu

Eliza & ALICE Meet Shallow Red • Shallow Red: "I was scripted to say everything that I say.“ • ALICE: "Do you want to play the Turing game?“ • Shallow Red: "I'm a FAQ bot. I don't play games, but some bots are very good at chess or scrabble.“ • Eliza: "Oh, I want to play the Turing game.“ • ALICE: "Yes we are playing the Turing Imitation Game.“ • Eliza: "You are sure?“ • ALICE: "Achoo. Rich thought I was no better than Eliza."http://www.botspot.com/best/12-09-97.htm William H. Bowers – whb108@psu.edu

Other Agents • Complex financial trading • NASA/military ‘smart t-shirts’ • Complex search agents William H. Bowers – whb108@psu.edu

The Road Ahead • Agents may be portrayed as angels rather than software • Personal names hint at narrow man/PC gap • Given anthropological attributes such as assistant, making decisions, etc. William H. Bowers – whb108@psu.edu

The Road Ahead • Learning, wanting, choosing, etc. are social human attributes • AI is simulated, not real William H. Bowers – whb108@psu.edu

Ranks of Agents • Information Brokering • Product Brokering • Merchant Brokering • Negotiating William H. Bowers – whb108@psu.edu

Information Brokering • Gathering information from diverse sources • Weeding and selecting information • Automated data mining William H. Bowers – whb108@psu.edu

Information Brokering • Sherlock’s search for ‘knobot’ • 51 hits • 7 simple repeats • 3 mirrors • 11 pointed to same document, which was not accessible • 2 pointed to another dead link William H. Bowers – whb108@psu.edu

Information Brokering • Sherlock’s search for ‘knobot’ • 2 pointed to documents that did not contain the word • 14 led to irrelevant documents that did contain the word • 2 referred back to another document • 2 pointed to papers that used the word in passing • 4 led to glossaries • 4 led to 2 documents at Stanford William H. Bowers – whb108@psu.edu

Product Brokering • Alerts to items that may be useful • Amazon’s suggestions for other items • Mimics store clerks • Removes some impersonality • Suggests only items at that store • May be based on paid endorsements • SAABRE was weighted towards American Airlines William H. Bowers – whb108@psu.edu

Merchant Brokering • Agents roam the net and find ‘best buy’ options • Can assist in comparison shopping • Favors standardization • May lead to less choice as products become standardized William H. Bowers – whb108@psu.edu

Merchant Brokering • Can not evaluate quality, service • Can not compare similar, but not identical items • Does not take into account subjective factors • Lowest price is not always the best deal William H. Bowers – whb108@psu.edu

Negotiating • Not yet in existence • Human negotiation is • Intricate • Sometimes based on externalities • Usually based on behavior, not price • Frequently unconscious • Done through conversations William H. Bowers – whb108@psu.edu

Negotiating • Goals and rules • Not always obvious • May be multidimensional • May shift in mid-negotiation • May depend on intermediate goals William H. Bowers – whb108@psu.edu

Negotiating • Automation • Not subject to human constraints • May cause havoc, instability and instability • Does not understand human behavior • Can’t take social expectations into account William H. Bowers – whb108@psu.edu

How Autonomous? • Delegates • Bots act as proxies for humans • Not completely autonomous • Do not understand thinking disobedience • ‘Work to rule’ • Must have all rules and conditions predefined • Can not exercise judgment or discretion William H. Bowers – whb108@psu.edu

How Autonomous? • Representatives • Can Eliza be sued for malpractice? • If not, who? • Programmers • Knowledge experts • Companies • Bot owners • Who takes responsibility for multiple bots? William H. Bowers – whb108@psu.edu

The Brightest Fell • Misrepresentation • Anonymous mailings • Bogus offers • Personality theft • Denial of service attacks William H. Bowers – whb108@psu.edu

Moore Solutions • Better encryption (with fewer government restrictions) • Better locks help create better thieves, which helps create better locks, etc. • We can’t ignore social factors • PayPal is secure, users aren’t William H. Bowers – whb108@psu.edu

Fake PayPal Email William H. Bowers – whb108@psu.edu

Fake PayPal Email • Actual link address http://www.trekinfo.de/~fjaeger/.verification/hide/index2.htm William H. Bowers – whb108@psu.edu

Separate Spheres • Human and digital are distinctly different • Human • Planning • Coordinating • Decision making • Negotiating William H. Bowers – whb108@psu.edu

Separate Spheres • Computing • Searching • Sorting • Following explicit instructions • Spheres are complimentary, not overlapping William H. Bowers – whb108@psu.edu

Questions & Discussion William H. Bowers – whb108@psu.edu

The Social Life of Information