by From Gregory Daneke and RWER issue 93 The global financial crisis that began in earnest in 2008 (and is yet to be resolved) prompted significant challenges to the theory and methods of mainstream or orthodox (also known as Neoclassical and/or Neoliberal) economics. Even distinguished orthodox economists, Paul Krugman (2009) Joseph Stiglitz (2017), and Paul Romer (2020) have joined with the crescendo of obscure, yet profound, voices, such as: “institutionalist” (e.g. Hodgson, 2004), “heterodox” (e.g. Keen, 2001; and E. Smith, 2010), and “ecological” (e.g. Constanza, et al., 1997; and Fullbrook and Morgan, 2019), as well as Marxist economists. One especially promising alternative to mainstream economics grew out of work in nonlinear dynamics and systems theory (see, Daneke, 1999), and
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from Gregory Daneke and RWER issue 93
The global financial crisis that began in earnest in 2008 (and is yet to be resolved) prompted significant challenges to the theory and methods of mainstream or orthodox (also known as Neoclassical and/or Neoliberal) economics. Even distinguished orthodox economists, Paul Krugman (2009) Joseph Stiglitz (2017), and Paul Romer (2020) have joined with the crescendo of obscure, yet profound, voices, such as: “institutionalist” (e.g. Hodgson, 2004), “heterodox” (e.g. Keen, 2001; and E. Smith, 2010), and “ecological” (e.g. Constanza, et al., 1997; and Fullbrook and Morgan, 2019), as well as Marxist economists.
One especially promising alternative to mainstream economics grew out of work in nonlinear dynamics and systems theory (see, Daneke, 1999), and has been enhanced by huge advances in computational capabilities. This approach, under the catch-all rubric of Complexity Studies, has many variegated and partial offshoots both mathematical and metaphorical. Plus, use of its computational tools is no guarantee of theoretical coherence. Some qualitative applications are especially robust and some quantitative pieces linger too close the event horizons of neoclassical black holes. Nonetheless, at its core, complexity is a completely unique worldview (see, Arthur 2013) with far reaching implications for how economies are studied and policies derived. As one might expect, mainstream economics, has been extremely reluctant to accept these implications and has only tangentially toyed with the isolated elements of the complexity approach. As in the past (e.g. game theory, behavioral economics, etc.), mainstreamers merely graft-on certain tools and concepts without altering their archaic foundations or their ideological commitments. This highly selective retention is made more problematic by recent developments in Artificial Intelligence (AI) and BIG DATA.
AI is primarily about the use of computer algorithms to augment and/or replace human judgements. AI applications have expanded of late given the massive explosions of data collection and manipulation by the mammoth internet monopolies (e.g. Google, Facebook, Amazon, Baidu, WeChat, etc.) and government agencies. This Big Data era poses a number of its own threats in an economy already riddled with dysfunctions, and has compounded fears about AI. Some apprehensions are overblown and some remain under appreciated. AI is unlikely to bring the science fiction terror, in which killer robots become sentient and end humanity, but it does harbor the potential for dramatic immiseration. One of the vastly underestimated by-products of AI expansion is that it will further retard the development of economic theory and practice, and indirectly exacerbate social upheaval. read more