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THESIS PROJECT, Human-in-the-loop (HITL) computing Human-in-the-loop…

- - - - The 10 most cited AI data sets are riddled with label errors,
    - - Evidence that there are extensive technical skills in AI in UK research institutions as demonstrated by research publications. less evidence that these skills are being used in applications in creative industries
        
        Not sure how to implement AI into creative industries
        
        Can more familiar interaction or interface will help the user with their learning
      - Fast developments
      - has become a continuous problem
      - affects both employers as well as current and future workforce
    - - WHAT IS efficiency?
      - Creation???
- - - - Physical Data / Information
- - - - Amplifier
        
        Mismach objections between computer and humans
    - - What are we trying to optimise for?
        
        Preference Learning
        Expose people objectives. Figure out what their reward functions are :
        
        Grow someones reward function
        Good mentor exposes you to additional opportunities. You might have something you currently want but are not aware of other optiions.
- - - - Understandability
  - - - The reason why not successful at creating strong intelligent is because we do not know how we function and we are trying to build computers in the image of the human
    - - Continuous improvement of machine learning and deep learning models requires people for data labeling, quality control (QC), and modeling.
      - Automation can speed the development process but it requires people to build, maintain, and monitor exceptions.
      - People design the processes that integrate an AI solution into an organization.
      - When AI models fail, people must step in to mitigate risk and resolve problems.
- - - - The patterns of how these sense, the information we need to understand and operate smoothly, and what we expect to do, all change depending on whether we’re having a conversation at a party, jogging down a path, driving a car, or reading a text come together are called modalities.
        
        Understanding these combinations is essential to designing the next generation of user experiences, like VR, Voice, and sensor-based IoT experiences well.
        
        It can also address some of the ways in which digital experiences have become detrimental to our real world lives.
        
        But it also can improve the way we design experiences for all of the different kinds of products and media being created now.
        
        If something is experienced in several senses it’s judged to be more real, we are more certain about it, and the experience or information is more memorable.
        
        Second, having multiple sensory options is important because one sense might not be working for someone, either temporarily or permanently.