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  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0000-0003-0757-275X"
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   "@id": "https://wulfkaal.github.io/claims/2808132-001",
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   "text": "Regulation is usually reactive because it responds to facts, but the current environment is one of data rather than settled facts; regulation must therefore become proactive and dynamically responsive to data and trends.",
   "abstract": "Disruptive innovation creates increasing regulatory challenges. The reason for this is simple: Regulation is usually reactive, responding to facts. However, we currently live in a world of data, not facts. Regulation must therefore be proactive and dynamically",
   "citation": "Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132",
   "datePublished": "2016",
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   "text": "A more granular assessment of venture capital investments in Big Data and software as a service can provide regulators with much needed feedback on the regulatory needs associated with those areas.",
   "abstract": "8-11 below. A more granular assessment of the VC investments in Big Data and SaaS can provide much needed feedback for regulators on associated regulatory needs.",
   "citation": "Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132",
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   "text": "Increasing the quantity of data does not dissolve the foundational methodological problems of data: construct validity, measurement, reliability, and data dependencies remain the same regardless of how much data is collected.",
   "abstract": "Foundational data issues of construct validity, measurement, reliability, and data dependencies are the same regardless of data quantities.",
   "citation": "Mark Fenwick, Wulf A. Kaal, Erik P. M. Vermeulen, Regulation Tomorrow What Happens When Technology Is Faster Than the Law (2017). SSRN: https://ssrn.com/abstract=2834531",
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   "text": "The extent to which a company uses data and algorithms will separate the winning companies of the future from the rest, because algorithmically driven firms gather consumer behavior data and instantaneously feed it back into an improved consumer experience.",
   "abstract": "The use of data and algorithms will distinguish the successful companies of the future. Algorithmically-driven companies use new and emerging technologies to gather data from their consumers about their behavior and then instantaneously utilize this information to improve the consumer experience.",
   "citation": "Mark Fenwick, Wulf A. Kaal, Erik P. M. Vermeulen, The ‘Unmediated’ and ‘Tech-Driven’ Corporate Governance of Today's Winning Companies (2017). SSRN: https://ssrn.com/abstract=2922176",
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   "text": "Leveraging the big data collected through Legal Tech solutions and blockchain applications in combination with machine learning produces more creative and faster tools, which in turn generates a surge of innovative platforms that disrupt the legal industry.",
   "abstract": "Leveraging the big data that is collected by using Legal Tech solutions and blockchain applications in combination with machine learning creates more creative and faster tools.",
   "citation": "Mark Fenwick, Wulf A. Kaal, Erik P. M. Vermeulen, Legal Education in the Blockchain Revolution (2017). SSRN: https://ssrn.com/abstract=2939127",
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   "text": "The majority of private fund advisers that deploy blockchain technology, artificial intelligence, and big data in their operations or strategy charge their investors lower fees, even though not all blockchain enabled funds charge per transaction fees.",
   "abstract": "While not all blockchain-enabled private investment funds charge per-transaction fees, the majority of private fund advisers that use blockchain technology, artificial intelligence, and big data in different aspects of their operations or strategy charge their investors lower fees.",
   "citation": "Wulf A. Kaal, Blockchain Applications and Fee Structure Developments in Private Investment Funds (2017). SSRN: https://ssrn.com/abstract=2959730",
   "datePublished": "2017",
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   "text": "The rise of blockchain applications in private investment funds can exacerbate the industry's already changing fee structure.",
   "abstract": "The paper has illustrated that the rise of blockchain applications in private investment funds can exacerbate the already changing fee structure of the industry.",
   "citation": "Wulf A. Kaal, Blockchain Applications and Fee Structure Developments in Private Investment Funds (2017). SSRN: https://ssrn.com/abstract=2959730",
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   "text": "Anecdotal evidence suggests that the majority of private fund advisers who use blockchain, artificial intelligence, and big data in their operations or strategy charge substantially lower fees than advisers who do not use these technologies.",
   "abstract": "Anecdotal evidence suggests that the majority of private fund advisers that use blockchain technology, artificial intelligence, and big data in different aspects of their operations or strategy have a substantially lower fee structure than those who do not use them.",
   "citation": "Wulf A. Kaal, Blockchain Innovation for Private Investment Funds (2017). SSRN: https://ssrn.com/abstract=2998033",
   "datePublished": "2017",
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   "text": "Whether private investment funds succeed in disintermediating banks through blockchain implementation depends on their ability to find scale opportunities.",
   "abstract": "Private investment funds' bank disintermediation through the implementation of blockchain technology will depend on their ability to find scale opportunities.",
   "citation": "Wulf A. Kaal, Marco Dell'Erba, Blockchain Innovation in Private Investment Funds - A Comparative Analysis of the United States and (2017). SSRN: https://ssrn.com/abstract=3002908",
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   "text": "Big data is often not the output of instruments designed to generate valid and reliable data suitable for scientific analysis, so foundational data quality problems persist regardless of how much data is collected.",
   "abstract": "Big data is often not the output of instruments designed to generate valid and reliable data suitable for scientific analysis.",
   "citation": "Wulf A. Kaal, Decentralization - Past, Present, and Future (2019). SSRN: https://ssrn.com/abstract=3411897",
   "datePublished": "2019",
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   "text": "Big data and algorithmic data analytics enable centralized algorithmically automated systems such as Google, Facebook, and Amazon to know individuals' political preferences better than the individuals themselves.",
   "abstract": "Big data and algorithmic data analytics enable centralized algorithmically automated systems (such as Google, Facebook, and Amazon in the early 2020s) to know individuals' political preferences better than the individual's themselves.",
   "citation": "Wulf A. Kaal, How Decentralized Systems Can Upgrade AI (2021). SSRN: https://ssrn.com/abstract=3808867",
   "datePublished": "2021",
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   "text": "Centralized algorithmic automation, defined as artificially intelligent systems taking over core functions in human society, poses perhaps the greatest threat to decentralization.",
   "abstract": "Centralized algorithmic automation poses perhaps the greatest threat to decentralization. Centralized algorithmic automation describes the process of artificially intelligent systems taking over core functions in human society.",
   "citation": "Wulf A. Kaal, Decentralization Neutralizers (2021). SSRN: https://ssrn.com/abstract=3808873",
   "datePublished": "2021",
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 "description": "12 claims in the published works of Wulf A. Kaal carry the concept tag 'big-data'. Derived node: a roster, not an adjudicated definition."
}