The Disruptive Substitution of Human Capital by IT
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Sprache:Englisch
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Erscheinungsdatum
25.07.2017
Verlag
GRINSeitenzahl
59 (Printausgabe)
Dateigröße
1071 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9783668491052
Master's Thesis from the year 2017 in the subject Business economics - Economic Policy, grade: 2, , language: English, abstract: In the course of the last century the economy experienced a gradual shift from the primary and secondary to the tertiary sector. With the emergence of disruptive IT the service sector's traditional barriers are experiencing a fundamental erosion. In this context "disruptive IT" stands for big data, predictive analytics, machine learning and artificial intelligence. The overall hypothesis this thesis seeks to verify is "disruptive IT will substitute human capital to an extent that will irreversibly materialize in an unprecedented technological rate of unemployment".
The investigation commences with an analysis of unemployment statistics and a trend analysis over the last decades with the objective to reveal what could be perceived as technological hike of the natural rate of unemployment. It will be shown that historical data yet does not provide sufficient evidence to become scientifically convinced about the hypothesis laid out before . This does not come with surprise given the disruptive nature of recent IT advances which have yet only moderately started to unfold their full potential. Hence, disruption makes past-oriented statistics a second best guess of what to expect in future but suggests a rather simulation-based approach validated by expert opinion.
Therefore, we take a look at the contemporary study and analytical model of the Oxford researchers Carl B. Frey and Michael A. Osborne followed by the criticism of their criteria-based outside-in assessment on behalf of the Organisation for Economic Co-operation and Development (OECD). Next part of the discussion is the analysis of a recent report by the World Economic Forum (WEF) based on a self-assessment of industries' opinion leaders and field matter experts captured via means of employer survey. Finally, both the common denominator of as well as the key separators between the discussed material get consolidated and interpreted - with the distinction of the latter into those that arise out of methodological heterogeneity in contrast to those which relate to results and conclusions.
It's not academics' primary concern to make predictions and surely not part of their routine tasks. This master thesis wants to make a contribution to the way policymakers, employers and employees as well as the society as a whole shape the future and to serve with quantified substance as facilitator in nudging science to expand the comfort zone and rethink the frontiers of academically serious work.
The investigation commences with an analysis of unemployment statistics and a trend analysis over the last decades with the objective to reveal what could be perceived as technological hike of the natural rate of unemployment. It will be shown that historical data yet does not provide sufficient evidence to become scientifically convinced about the hypothesis laid out before . This does not come with surprise given the disruptive nature of recent IT advances which have yet only moderately started to unfold their full potential. Hence, disruption makes past-oriented statistics a second best guess of what to expect in future but suggests a rather simulation-based approach validated by expert opinion.
Therefore, we take a look at the contemporary study and analytical model of the Oxford researchers Carl B. Frey and Michael A. Osborne followed by the criticism of their criteria-based outside-in assessment on behalf of the Organisation for Economic Co-operation and Development (OECD). Next part of the discussion is the analysis of a recent report by the World Economic Forum (WEF) based on a self-assessment of industries' opinion leaders and field matter experts captured via means of employer survey. Finally, both the common denominator of as well as the key separators between the discussed material get consolidated and interpreted - with the distinction of the latter into those that arise out of methodological heterogeneity in contrast to those which relate to results and conclusions.
It's not academics' primary concern to make predictions and surely not part of their routine tasks. This master thesis wants to make a contribution to the way policymakers, employers and employees as well as the society as a whole shape the future and to serve with quantified substance as facilitator in nudging science to expand the comfort zone and rethink the frontiers of academically serious work.
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