Task 1 - M&M Flashcards

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1
Q

Keyword: Cognitive science

A
  • interdisciplinary study of mind and intelligence, embracing philosophy, psychology, artificial intelligence, neuroscience, linguistics, and anthropology
  • how we can study cognition over the aspects of human and further intelligence; how we can use technology to model human behaviour
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2
Q

Keyword: Artificial Intelligence (AI)

A
  • ability of non-biological mechanisms to accomplish goals
  • display intelligent behaviour
  • rationality
  • take best action to achieve a specific goal
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3
Q

Artificial

A

implies the synthetic or human-designed rather than the naturally derived; “artificial” of AI involves mechanics, electronics, or computers

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4
Q

Intelligence

A

ability to accomplish complex goals

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5
Q

Keyword: Prediction

A

ability to take information you have and generate information you didn’t previously have

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6
Q

Keyword: Prediction - how does it relate to AI?

A
  • task that makes AI abundant and inexpensive
  • key function of AI: forecasting significant events, appropriately characterizing the uncertainties inherent in such forecasts, and effectively communicating those probabilistic forecasts to stakeholders
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7
Q

What are the 3 laws of robotics?

A
  1. Never hurt a human being
  2. Always obey orders unless in conflict with law 1.
  3. A robot must protect its own existence unless in conflict with law 1 and 2.
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8
Q

What is the influence of AI on PSY?

A
  • Counseling : Simulation of a psychotherapist (ELIZA, PAARY and Eli);
  • virtual human patients used in clinical training and skill acquisition;
  • can be used in assessment, psychological treatments and testing;
  • virtual avatars providing info about mental health resources
  • AI health screening
  • Therapeutic computer games and exposure therapy
  • AI: Super clinicians (–> better than humans; with advanced sensory technologies; able to analyze subtle facial expressions) –> conduct sessions by themselves or as a help to human therapist
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9
Q

Advantages of AI

A

-clinical training and skill acquisition: receiving adaptive and customized training that is highly realistic and also available to the trainee at any time and freeing up humans to play a more advanced role
-virtual reality avatars: could be accessed remotely to provide psychological services to anywhere where there is an Internet connection;
 persons who are concerned about privacy and the stigma associated with seeking care in person may be more willing to seek help from a virtual care provider in the comfort of their home;
 it’s more interactive and engaging than websites
- AI assessments: more efficient and sophisticated because of the capability to process complex data, customize to the individual, and reduce uncertainty in screening outcomes
-can identify patterns, trends, and meaning from complex data that are too complex to be processed by humans or other computer-based technologies
-reduces human errors

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10
Q

Disadvantages of AI

A
  • induced unemployment, socioeconomic inequality, growing technological dependency, and human de-skilling
  • data security and privacy
  • power and influence that can be abused
  • lacks human qualities e.g. wisdom and compassion
  • interpersonal warmth and empathy are important for therapy
  • cultural differences must be considered
  • dangerous if AI becomes more intelligent than humans
  • automatized weapons and cyberwar
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11
Q

What is machine learning?

A

-one technique of AI
-rational
-involves just one component: prediction
-not the same as automation (–> automation also involves AI to be involved with data collection, judgment and action)
- we teach to exhibit human intelligence
-reinforcement learning, decision trees
==> Human- involved

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12
Q

What is deep learning?

A
  • one technique of machine learning
  • ability of computers to learn without being explicitly programmed
  • data-up approach: learns things by itself without being programmed by experts first
  • deep: multiple layers of neurons
  • more intelligent than our human understanding
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13
Q

Supervised learning

A

learns how to generalise from e.g. several pictures given

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14
Q

Unsupervised learning

A

learns things by itself

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15
Q

Reinforcement learning

A

Reinforced through human e.g. this match is good, this is not

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16
Q

What are 7 reasons why humans are bad at prediction?

A
  • Overestimate it in short- run but underestimate it in the long- run
  • You cannot refute an argument that its not magical –> not scientific and not falsifiable
  • Narrow competence
  • Misleading that people think it will be super fast, you need to prepare it by humans
  • Exponential; performance has to stop at some point
  • We ignore that the whole world is gonna change too; speed of development is slowed down
17
Q

What are different levels of AI?

A
  • specific AI

- Super AI/Super human