Ai and productivity
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Transcript of Ai and productivity
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How AI Can Help People Be More Productive at Work
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AI in the Workplace
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A Brief History of AI
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Dartmouth Workshop 1956
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every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it .
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"machines will be capable, within twenty years, of doing any work a man can do.”
Herbert Simon (1965)
“In from three to eight years we will have a machine with the general intelligence of an average human being.”
Marvin Minsky (1970)
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An AI Timeline
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1950 1960 1970 1980 1990 2010 20202000
Birth of AI
• Information Theory – digital signals• Cybernetics – thinking machines• The Turing Test• Symbolic reasoning
• Limited computer processing power• Limited database capacity • Limited networking capabilities• Real-world problems are complicated
- Image processing / face recognition- Combinatorial explosion
AI Winter
• Expert Systems (knowledge) • Neural networks make a comeback • Optical character recognition• Speech recognition
• Disappointing results• Collapse of dedicated hardware vendors
• Machine learning• Deep learning – pattern analysis / classification
- Big data: large databases - Fast processors to crunch data- High-speed networks
Focus on Specific ‘Intelligence’ Focus on Specific Problems
AI Winter II
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Where Are We Today?
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Natural Language Processing (NLP)
Machine Learning
Results
Key Elements of Contemporary AI
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AI Achievements are Impressive
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But, AI Has Not Achieved the Original Vision
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The Goals of AI Have Evolved
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Emulate humans Assist / replace humans for dedicated applications
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So Today, AI Is Effective When….
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All relevant data is available to consider
The desired outcome is predictable
The rules are clear
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AI in CollaborationPlatform Vendors Embrace AI Bots
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Example/Pizza Ordering Bot
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• Pizza size – M, L, XL• Pizza toppings
- Onions- Peppers- Tomatoes- ….
• Delivery address• Delivery time• Method of payment
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A Modern Approach to AI
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Artificial Intelligence (AI)
To build human-like capabilities into autonomous technological systemssuch as a computer or robot
Douglas Engelbart, 1962
Intelligence Augmentation (IA)
To increasing the capability of a person to approach a complex problem situation, to gain comprehension to suit their particular needs, and to derive solutions to problems.”
Douglas Engelbart, 1962
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Artificial Intelligence vs. Intelligence Augmentation
AI Puts Technology at the Core IA Puts Humanity at the Core
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Example:Email-based Topic Computing
Information Delivered the Way the Brain Works
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Many DisconnectedCloud Apps
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• Singular proper nouns (NNP) becomes topic candidates, excluding dates, numbers, locations and people’s names
• First word algorithm (matched against common dictionary)
• Capitalized nouns are included
Natural Language Processing (NLP) Example Part of Speech
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• How often does a topic appear in different sources (i.e. apps)?
• How many times does a topic appear in a given app?
• When was the last time the topic appeared?
• How often does the topic appear for my colleagues?
• How much have my colleagues interacted with a specific topic?
Machine Learning Example
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People and technology work best, when they work together
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Thank You