Artificial Intelligence, the Singularity, Critical Thinking and Public Policy Realisation Policy Reflections in the Rarefied Ambience of Erudite & Jurisdictive Milieu RL Vol XIII No 611 MMXVII (original) (raw)

2019, Respublica Litereria

Governments have much to gain from applying algorithms to public policy, but controversies loom. Machine-learning systems excel at prediction. A common approach is to train a system by showing it a vast quantity of data on, say, students and their achievements. The software chews through the examples and learns which characteristics are most helpful in predicting whether a student will drop out. Once trained, it can study a different group and accurately pick those at risk. By helping to allocate scarce public funds more accurately, machine learning could save governments significant sums Habermas differentiates three primary generic cognitive areas in which human interest generates and interprets knowledge-termed knowledge constitutive, determining the mode of discovering knowledge as well as whether knowledge claims can be warranted. These areas define cognitive interests (learning domains) grounded in unique aspects of social existence-work, interaction and power. Much of the historical-hermeneutic disciplines belong to the domain of the practical, while the emancipatory domain identifies self-knowledge or self-reflection-interest in the way one sees oneself, one's roles and social expectations. On the other hand, the 21st century will be dominated by algorithms, arguably the single most important concept in our world. Natural algorithms have ruled every century with life in it since Darwin discovered the fundamental algorithm of evolution. Out of that dumb process-logic, arises all the intelligence and complexity of all living systems. Algorithmic forces exist and exert their powers in systemic and relational ways; they are not driven by isolatable and intrinsic traits. They require sequential steps, built from iterative if-then-else logic, driven by richer information processes than physical forces. Closely associated with this is the Singularity, an era in which intelligence will become increasingly non-biological and trillions of times more powerful than it is today. It heralds the dawning of a new civilization that will enable people to transcend biological limitations amplifying their creativity. It emerges from Artificial Intelligence that denotes electronic, digital, virtual or other non-biological and/or disembodied entities, which exhibit the function of intelligence. Machine-learning systems excel at prediction and governments have much to gain from applying algorithms to public policy, but controversies loom. (The Economist, 2016). Nevertheless, what does such critical thinking, singularity, algorithmic forces & artificial intelligence have to do with public policy-a legal, ethical & moral dispensation by the executive branch of government, but emerging from constitutional, legislative and administrative laws, vis-à-vis a class of issues in a manner consistent with institutional customs? Keywords: critical thinking, algorithm, singularity, artificial intelligence public policy,