In five experiments (N = 3,828), we investigate whether people prefer investment decisions to be made by human investment managers rather than by algorithms ("robos"). In all of the studies we investigate morally controversial companies, as it is plausible that a preference for humans as investment managers becomes exacerbated in areas where machines are less competent, such as morality. In Study 1, participants rated the permissibility of an algorithm to autonomously exclude morally controversial stocks from investment portfolios as lower than if a human fund manager did the same; this finding was not different if participants were informed that such exclusions might be financially disadvantageous for them. In Study 2, we show that this ro...
Purpose: This research set out to examine how financial advice provided by a human advisor (vs robo-...
Purpose – Considering the increasing impact of Artificial Intelligence (AI) on financial technology ...
Investors increasingly use machine learning (ML) algorithms to support their early stage investment ...
In five experiments (N = 3,828), we investigate whether people prefer investment decisions to be mad...
Artificial intelligence, or AI, enhancements are increasingly shaping our daily lives. Financial deci...
The ongoing institutional debate wonders whether robo advice may potentially bridge the advice gap, ...
We study the introduction of robo-advising on a large representa-tive sample of Employee Saving Plan...
We use a unique data set covering brokerage accounts for a large cross-section of investors over a s...
In light of the emergence of artificial intelligence in financial technology and the fourth industri...
Robo-advisors are novel tools in financial markets that provide investors with low-cost financial ad...
Owing to technological advancements, individuals can increasingly automate and delegate private deci...
Technological advancements bring continuous changes into the investment industry. The paper aims to ...
We propose an experimental study to examine how to optimally design a robo-advisor for the purposes ...
Adaptive online platforms, powered by artificial intelligence, commonly referred to as robo-advice, ...
The fast development of robo-advice has responded to a growing demand for automation and enhanced ca...
Purpose: This research set out to examine how financial advice provided by a human advisor (vs robo-...
Purpose – Considering the increasing impact of Artificial Intelligence (AI) on financial technology ...
Investors increasingly use machine learning (ML) algorithms to support their early stage investment ...
In five experiments (N = 3,828), we investigate whether people prefer investment decisions to be mad...
Artificial intelligence, or AI, enhancements are increasingly shaping our daily lives. Financial deci...
The ongoing institutional debate wonders whether robo advice may potentially bridge the advice gap, ...
We study the introduction of robo-advising on a large representa-tive sample of Employee Saving Plan...
We use a unique data set covering brokerage accounts for a large cross-section of investors over a s...
In light of the emergence of artificial intelligence in financial technology and the fourth industri...
Robo-advisors are novel tools in financial markets that provide investors with low-cost financial ad...
Owing to technological advancements, individuals can increasingly automate and delegate private deci...
Technological advancements bring continuous changes into the investment industry. The paper aims to ...
We propose an experimental study to examine how to optimally design a robo-advisor for the purposes ...
Adaptive online platforms, powered by artificial intelligence, commonly referred to as robo-advice, ...
The fast development of robo-advice has responded to a growing demand for automation and enhanced ca...
Purpose: This research set out to examine how financial advice provided by a human advisor (vs robo-...
Purpose – Considering the increasing impact of Artificial Intelligence (AI) on financial technology ...
Investors increasingly use machine learning (ML) algorithms to support their early stage investment ...