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  2. Ethics of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Ethics_of_artificial...

    The ethics of artificial intelligence is one of several core themes in BioWare's Mass Effect series of games. [187] It explores the scenario of a civilization accidentally creating AI through a rapid increase in computational power through a global scale neural network. This event caused an ethical schism between those who felt bestowing ...

  3. AI and ethics: Business leaders know it’s important, but ...

    www.aol.com/finance/ai-ethics-business-leaders...

    MIT Sloan Management Review and Boston Consulting Group recently assembled a panel of AI academics and practitioners and the final question they asked was: “As the business community becomes ...

  4. Automated decision-making - Wikipedia

    en.wikipedia.org/wiki/Automated_decision-making

    Automated decision-making involves using data as input to be analyzed within a process, model, or algorithm or for learning and generating new models. [7] ADM systems may use and connect a wide range of data types and sources depending on the goals and contexts of the system, for example, sensor data for self-driving cars and robotics, identity data for security systems, demographic and ...

  5. Fairness (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Fairness_(machine_learning)

    Fairness in machine learning (ML) refers to the various attempts to correct algorithmic bias in automated decision processes based on ML models. Decisions made by such models after a learning process may be considered unfair if they were based on variables considered sensitive (e.g., gender, ethnicity, sexual orientation, or disability).

  6. Big data ethics - Wikipedia

    en.wikipedia.org/wiki/Big_data_ethics

    Big data ethics, also known simply as data ethics, refers to systemizing, defending, and recommending concepts of right and wrong conduct in relation to data, in particular personal data. [1] Since the dawn of the Internet the sheer quantity and quality of data has dramatically increased and is continuing to do so exponentially.

  7. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Then, analyze the source data to determine the most appropriate data and model building approach (models are only as useful as the applicable data used to build them). Select and transform the data in order to create models. Create and test models in order to evaluate if they are valid and will be able to meet project goals and metrics.

  8. AAAI/ACM Conference on AI, Ethics, and Society - Wikipedia

    en.wikipedia.org/wiki/AAAI/ACM_Conference_on_AI...

    The conference is jointly organized by the Association for Computing Machinery, namely the Special Interest Group on Artificial Intelligence (SIGAI), and the Association for the Advancement of Artificial Intelligence, and "is designed to shift the dynamics of the conversation on AI and ethics to concrete actions that scientists, businesses and ...

  9. Data classification (business intelligence) - Wikipedia

    en.wikipedia.org/wiki/Data_classification...

    In business intelligence, data classification is "the construction of some kind of a method for making judgments for a continuing sequence of cases, where each new case must be assigned to one of pre-defined classes." [1] Data Classification has close ties to data clustering, but where data clustering is descriptive, data classification is ...

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