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2#15 - The Business Impact of Data Ethics (Eng)

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Manage episode 362699617 series 2940030
Innhold levert av Winfried Adalbert Etzel - DAMA Norway. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Winfried Adalbert Etzel - DAMA Norway eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

«Infants with guns!»

Are we mature enough to track, collect and handle data responsibly, according to ethical standards? I talked with Director of Data Innovation at IIH Nordic Steen Rasmussen about the Business impact of Data Ethics.

Here are my key take aways:

  • If were track, collect, and keep all data for any random opportunistic purpose, we put your companies at risk.
  • This includes a «commercial curse» of budget-heavy tracking and budget-light management and business value creation through data.
  • ROT, Norwegian for clutter, is an acronym for Redundant, Obsolete, Trivial - the dat that clutters your way to find valuable data.
  • Collection and tracking of data is still too much dependent on people: If there is a change in personal, you get situations where new people «clutter the clutter»

Marketing & Sales

  • For many companies it was Marketing & Sales that drove the data-driven agenda.
  • The big value of Marketing & Sales is to add the market-dimension to the data.
  • You can actually relate your product to the market, ship to where the market is.
  • Analyzing market data is «putting a fixed entity on a moving target». The market changes to rapidly to provide good analysis.
  • The more you push behavioral forecasting into the future, the bigger your uncertainty.

Business value & Ethics

  • Corporate irresponsibility is an issue.
  • Sometimes we get involved in a projects for the projects sake.
  • Data projects have for a long time been theoretical, so the impact was not visible.
  • Chat-GPT is a black box. Should we really give it more firepower, if we don’t know how it works?
  • The market determines that there is a business value in being first.
  • The speed of innovation doesn’t give time for reactive regulatory bodies to regulate efficiently.
  • Companies need data ethical guidelines to say, how they will, shall and can use data.
  • Who should define data ethical guidelines in a company? It is still done on a user-level, whilst senior management is looking at market situations and weighting them against ethical guidelines.
  • We need regulatory and top-level guidelines that cannot be bent according to market situations.
  • «Ideally, but highly unlikely we need a global set of data ethical guidelines.»
  • The more trustworthy you are as a company, the more relevant data is shared with you.
  • With that trust and data, you can understand the market better than companies that are not trustworthy and basically flying blind.
  • Personal Data Literacy is important, and we need basic digital skills in our society.
  • There is also a lack of understanding, when it comes to measures set in place for peoples benefit, eg. Cookie-banners.
  • We are still lacking good privacy approved alternatives to the tools we are using on an everyday basis.
  • Everyone has to follow ethical guidelines. We cannot have a DarkOps department in our company.
  • Data Ethics guidelines should be something everyone can refer to.
  • Ask yourself: What is the minimum of data we require to collect? Anything else should become an ethical question.

Data Protection Laws:

  • There is a difference between the interpretation of regulations in the EU.
  • Nordic countries interpret law relatively, is this just, fair, reasonable?
  • Southern European countries use a more napoleonic or dogmatic approach, where «the law is the law, and the law must be obeyed.»
  • Both Chat-GPT and Google Analytics have been handled differently by data protection authorities.
  • Data Protection Authorities generalize to much, and don’t look at differences in technology.
  • Is a strict, generalized interpretation creating panic, for users of eg. Google Analytics?
  continue reading

58 episoder

Artwork
iconDel
 
Manage episode 362699617 series 2940030
Innhold levert av Winfried Adalbert Etzel - DAMA Norway. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Winfried Adalbert Etzel - DAMA Norway eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

«Infants with guns!»

Are we mature enough to track, collect and handle data responsibly, according to ethical standards? I talked with Director of Data Innovation at IIH Nordic Steen Rasmussen about the Business impact of Data Ethics.

Here are my key take aways:

  • If were track, collect, and keep all data for any random opportunistic purpose, we put your companies at risk.
  • This includes a «commercial curse» of budget-heavy tracking and budget-light management and business value creation through data.
  • ROT, Norwegian for clutter, is an acronym for Redundant, Obsolete, Trivial - the dat that clutters your way to find valuable data.
  • Collection and tracking of data is still too much dependent on people: If there is a change in personal, you get situations where new people «clutter the clutter»

Marketing & Sales

  • For many companies it was Marketing & Sales that drove the data-driven agenda.
  • The big value of Marketing & Sales is to add the market-dimension to the data.
  • You can actually relate your product to the market, ship to where the market is.
  • Analyzing market data is «putting a fixed entity on a moving target». The market changes to rapidly to provide good analysis.
  • The more you push behavioral forecasting into the future, the bigger your uncertainty.

Business value & Ethics

  • Corporate irresponsibility is an issue.
  • Sometimes we get involved in a projects for the projects sake.
  • Data projects have for a long time been theoretical, so the impact was not visible.
  • Chat-GPT is a black box. Should we really give it more firepower, if we don’t know how it works?
  • The market determines that there is a business value in being first.
  • The speed of innovation doesn’t give time for reactive regulatory bodies to regulate efficiently.
  • Companies need data ethical guidelines to say, how they will, shall and can use data.
  • Who should define data ethical guidelines in a company? It is still done on a user-level, whilst senior management is looking at market situations and weighting them against ethical guidelines.
  • We need regulatory and top-level guidelines that cannot be bent according to market situations.
  • «Ideally, but highly unlikely we need a global set of data ethical guidelines.»
  • The more trustworthy you are as a company, the more relevant data is shared with you.
  • With that trust and data, you can understand the market better than companies that are not trustworthy and basically flying blind.
  • Personal Data Literacy is important, and we need basic digital skills in our society.
  • There is also a lack of understanding, when it comes to measures set in place for peoples benefit, eg. Cookie-banners.
  • We are still lacking good privacy approved alternatives to the tools we are using on an everyday basis.
  • Everyone has to follow ethical guidelines. We cannot have a DarkOps department in our company.
  • Data Ethics guidelines should be something everyone can refer to.
  • Ask yourself: What is the minimum of data we require to collect? Anything else should become an ethical question.

Data Protection Laws:

  • There is a difference between the interpretation of regulations in the EU.
  • Nordic countries interpret law relatively, is this just, fair, reasonable?
  • Southern European countries use a more napoleonic or dogmatic approach, where «the law is the law, and the law must be obeyed.»
  • Both Chat-GPT and Google Analytics have been handled differently by data protection authorities.
  • Data Protection Authorities generalize to much, and don’t look at differences in technology.
  • Is a strict, generalized interpretation creating panic, for users of eg. Google Analytics?
  continue reading

58 episoder

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