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（北京）股份有限公司
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As artificial intelligence (Al)takes off,how do we efficiently integrate it into our lives and our
work Bridging the gap between promise and practice,Jann Spiess,an associate professor at
Stanford Graduate School of Business,is exploring how algorithms (can be designed to most
effectively support-rather than replace-human decision-makers.
"We don't have much work-yet-that takes design of the human-AI interface really seriously,"
says Spiess."Our debate about AI and the capabilities of AI is really misplaced,because it's all about
'Is AI better than the human "",he continues."I think instead we should be asking,'What are the
complementary(互补的)uses of AI ,
If users rely too heavily on an algorithm,they may ignore relevant context or information the
algorithm may not know.On the other hand,if users view recommendations as overly complex or
irrelevant,they may dismiss them altogether,forgoing any advantages algorithmic recommendations
may provide.
"Therefore,the best algorithm should take into account how a human will interact with the
information it provides,"Spiess says.In a rccent paper,Spiess outlines a conceptual (design
framework modeling how humans respond to algorithmic recommendations-and presents a
different approach to building Al tools.This approach is known as complementarity.
The researchers tested different recommendation strategies in an experiment,where participants
made 25 hiring decisions with different levels of algorithmic assistance.People using a
complementary algorithm-which offered selective recommendations in cases where a human was
likely to be uncertain or incorrect--made the most accurate decisions,outperforming those using a
purely predictive algorithm and those using no algorithmic support.
It's an encouraging result."There's much promise around AI improving decisions,"says Spiess,
who's particularly interested in applications that affect how services are allocated (in
resource-limited environments,such as placing teachers in underserved school districts with limited
budgets."If you could use algorithms to improve resource allocation,there are many high-value use
cases in areas where we don't have ready or clear solutions,"he says.
32.What is the main issue with current Al debates according to Spiess
A.Ignoring the potential of AI.
B.Overemphasis on AI's superiority.
C.Misunderstanding Al's purpose.
D.Lack of focus on Al's efficiency.
33.What can be inferred from Paragraph 3
A.Over-reliance on algorithms gives users more information.
B.Seeing algorithm recommendations as irrelevant may make users miss benefits.
C.Full trust in algorithms helps avoid all decision mistakes.
D.Questioning algorithm complexity drives users to improve algorithms.
34.What does Spiess think is the key to effective AI design
A.Enhancing algorithm complexity.
B.Reducing human dependence on AI.
C.Considering human-AI interaction
D.Improving AI's independent capability.
35.What does the experiment on hiring decisions show
A.Predictive algorithms were the most helpful.
B.Human judgment alone was the most accurate.
C.No algorithmic support was completely the best
D.Complementary algorithms were highly effective.
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