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Contenu fourni par Paul Richards & Joe Wiggins, Paul Richards, and Joe Wiggins. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Paul Richards & Joe Wiggins, Paul Richards, and Joe Wiggins ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
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Pants on fire

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Manage episode 424366545 series 3466363
Contenu fourni par Paul Richards & Joe Wiggins, Paul Richards, and Joe Wiggins. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Paul Richards & Joe Wiggins, Paul Richards, and Joe Wiggins ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Lying – it’s something that all humans do. Most of the lies we tell are small and harmless. But deceptive behaviour in the investment industry lowers trust and increases costs and complexity.

We are deceptive for many reasons and one of them is that we can get away with it. This is because, despite what we might believe, most of us are pretty terrible at spotting lying – including highly experienced financial analysts.

But what would happen if we all had access to AI-powered technology on our phones that could spot deception with a high degree of accuracy? Would that change how the industry behaves?

This is no idle speculation – in this episode of Decision Nerds, we explore research that suggests that AI is significantly better at spotting lying than humans. And as we all know, AI has a habit of surprising us by appearing in the wild far faster than we might expect.

How would this technology impact the investment industry? We discuss:

𝙏𝙝𝙚 𝙢𝙤𝙩𝙞𝙫𝙖𝙩𝙞𝙤𝙣 𝙛𝙤𝙧 𝙙𝙚𝙘𝙚𝙥𝙩𝙞𝙤𝙣 𝙞𝙣 𝙩𝙝𝙚 𝙞𝙣𝙙𝙪𝙨𝙩𝙧𝙮 – the entirely logical reasons that we don’t always tell the truth

𝘿𝙞𝙛𝙛𝙚𝙧𝙚𝙣𝙩 𝙠𝙞𝙣𝙙𝙨 𝙤𝙛 𝙙𝙚𝙘𝙚𝙥𝙩𝙞𝙤𝙣 𝙖𝙣𝙙 𝙩𝙝𝙚𝙞𝙧 𝙧𝙚𝙡𝙖𝙩𝙞𝙫𝙚 𝙞𝙢𝙥𝙖𝙘𝙩𝙨 – what are the traps that managers fall into and why

𝙅𝙪𝙨𝙩 𝙝𝙤𝙬 𝙢𝙪𝙘𝙝 𝙗𝙚𝙩𝙩𝙚𝙧 𝙞𝙨 𝘼𝙄? – the results might surprise you

𝙒𝙤𝙪𝙡𝙙 𝙖 𝙩𝙧𝙪𝙩𝙝 𝙢𝙖𝙘𝙝𝙞𝙣𝙚 𝙙𝙚𝙨𝙩𝙧𝙤𝙮 𝙩𝙝𝙚 𝙞𝙣𝙙𝙪𝙨𝙩𝙧𝙮 𝙤𝙧 𝙢𝙖𝙠𝙚 𝙞𝙩 𝙗𝙚𝙩𝙩𝙚𝙧? – our take on ‘creative destruction’

𝙏𝙝𝙚𝙧𝙚’𝙨 𝙣𝙤 𝙩𝙧𝙪𝙩𝙝 𝙢𝙖𝙘𝙝𝙞𝙣𝙚 𝙮𝙚𝙩 - we discuss a few better questions that we can use today.
Affectiva facial recognition demo
Paper on analysts' ability to spot CEO deception
Paper on AI's ability to spot CEO deception
Lying on CVs

  continue reading

12 episodes

Artwork

Pants on fire

Decision Nerds

published

iconPartager
 
Manage episode 424366545 series 3466363
Contenu fourni par Paul Richards & Joe Wiggins, Paul Richards, and Joe Wiggins. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Paul Richards & Joe Wiggins, Paul Richards, and Joe Wiggins ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Lying – it’s something that all humans do. Most of the lies we tell are small and harmless. But deceptive behaviour in the investment industry lowers trust and increases costs and complexity.

We are deceptive for many reasons and one of them is that we can get away with it. This is because, despite what we might believe, most of us are pretty terrible at spotting lying – including highly experienced financial analysts.

But what would happen if we all had access to AI-powered technology on our phones that could spot deception with a high degree of accuracy? Would that change how the industry behaves?

This is no idle speculation – in this episode of Decision Nerds, we explore research that suggests that AI is significantly better at spotting lying than humans. And as we all know, AI has a habit of surprising us by appearing in the wild far faster than we might expect.

How would this technology impact the investment industry? We discuss:

𝙏𝙝𝙚 𝙢𝙤𝙩𝙞𝙫𝙖𝙩𝙞𝙤𝙣 𝙛𝙤𝙧 𝙙𝙚𝙘𝙚𝙥𝙩𝙞𝙤𝙣 𝙞𝙣 𝙩𝙝𝙚 𝙞𝙣𝙙𝙪𝙨𝙩𝙧𝙮 – the entirely logical reasons that we don’t always tell the truth

𝘿𝙞𝙛𝙛𝙚𝙧𝙚𝙣𝙩 𝙠𝙞𝙣𝙙𝙨 𝙤𝙛 𝙙𝙚𝙘𝙚𝙥𝙩𝙞𝙤𝙣 𝙖𝙣𝙙 𝙩𝙝𝙚𝙞𝙧 𝙧𝙚𝙡𝙖𝙩𝙞𝙫𝙚 𝙞𝙢𝙥𝙖𝙘𝙩𝙨 – what are the traps that managers fall into and why

𝙅𝙪𝙨𝙩 𝙝𝙤𝙬 𝙢𝙪𝙘𝙝 𝙗𝙚𝙩𝙩𝙚𝙧 𝙞𝙨 𝘼𝙄? – the results might surprise you

𝙒𝙤𝙪𝙡𝙙 𝙖 𝙩𝙧𝙪𝙩𝙝 𝙢𝙖𝙘𝙝𝙞𝙣𝙚 𝙙𝙚𝙨𝙩𝙧𝙤𝙮 𝙩𝙝𝙚 𝙞𝙣𝙙𝙪𝙨𝙩𝙧𝙮 𝙤𝙧 𝙢𝙖𝙠𝙚 𝙞𝙩 𝙗𝙚𝙩𝙩𝙚𝙧? – our take on ‘creative destruction’

𝙏𝙝𝙚𝙧𝙚’𝙨 𝙣𝙤 𝙩𝙧𝙪𝙩𝙝 𝙢𝙖𝙘𝙝𝙞𝙣𝙚 𝙮𝙚𝙩 - we discuss a few better questions that we can use today.
Affectiva facial recognition demo
Paper on analysts' ability to spot CEO deception
Paper on AI's ability to spot CEO deception
Lying on CVs

  continue reading

12 episodes

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