The problem of Infobesity?
Topic by Norma
Essay by Lawrence
The consensus seems to be that there is no difference in meaning and use between infobesity and information overload. Both terms seem to be used to describe a situation where we are inundated with information to the extent that we cannot make a well informed decision.
The problem of infobesity is that information can become toxic and thus affect our ability to make the correct decision. In an article (1) by by Paul Rogers, Rudy Puryear and James Root “Infobesity: The enemy of good decisions” they write, “But the torrent that flows through most organizations today acts like so much bad cholesterol, clogging their arteries and slowing their reactions.”
Therefore, what are the issues for us in this debate? As far as philosophy is concerned, the primarily issue is an epistemology problem: what is knowledge and how do we distinguish knowledge from irrelevant information and false beliefs. Furthermore, how do we distinguish useful information from toxic to false information?
If we must, however, distinguish between information overload and infobesity I would venture the following explanation. I would argue that information overload could be used to describe the gross quantity of information we have to handle to make a reasonable decision. This is just a matter of quantity of information (quantitative) and not a matter of quality (qualitative) of the information. Information overload may or may not include useful information or toxic information.
Infobesity, as this buzzword suggests and the various articles on the subject argue, should be applied to information that includes toxic type of information. And by toxic we can include inconclusive or weak research to straight forward fake and false information including propaganda and manipulation. In other words, infobesity is the type of information that might negatively affect us in our endeavours. This is not to say we do not have access to reliable information, but rather the toxic information may affect us directly or indirectly in our purposes.
An underlying term that is relevant for us is the term, information redundancy. Redundancy is an important factor in epistemology precisely because it is part of the foundation of information and knowledge. The more confirmed information we have the better, but we need to be careful about the sources of this redundancy.
Information redundancy is always a matter of the quality of information rather than the quantity. A key factor of redundancy is that the source and “extraction” of information must be independent from other sources. This is why reproducibility is a key objective in science, even if sometimes this might be difficult to do. One might argue that objectivity is a key factor for information redundancy.
I would argue that objectivity links directly to the methodology of gathering data and information, and this is the first filter that turns raw data into useful data followed by the creation of information. However, for practical purposes it is always a balance between quantity and quality of information and processing the raw data.
To take a very modern example, today we all have a mobile phone with a decent camera. However, the quality of camera photos directly depends on the processor of the raw data coming from the sensor and the capacity of the mobile phone to manage data. Whilst we are usually happy with most phone images, the best images are usually those taken under ideal light condition and the sophistication of the technology. A low quality image is still an image but the scope might be very limited.
My point about this example is that although the technology might be objective it does not follow that the quality part of this technology is universal across all platforms. This idea might affect AI systems in the future.
Independence is a real factor for information and knowledge. Maybe this is the most important factor that might affect our day to day life today. In infobesity and information overload we have a problem of what information to trust because the consequences may be fatal. In politics we only need to mention the criminal disaster of brexit that was a pure political exercise in lies, misinformation, manipulation, and worse of all, ignorance.
Another factor that affects information and knowledge are mistakes and errors or even negative results in academia, which I will include as part of mistakes. Our knowledge system and culture abhors mistakes to the extent that our survival instincts make us prefer to continue with mistakes rather than speak out and identify mistakes.
No doubt, this abhorrence to mistakes stems from millennia of punishment and personal responsibility in religions and political systems with religious dogma at their base. The aviation industry seems to move away from this mind set quite professionally by trying to identify the causes of accidents rather than apportion responsibility.
Of course, I am not arguing that we should not hold people accountable for their mistakes, but only mistakes done through negligence or criminal intent that affects others. The main purpose of mistakes should be to learn from them and people affected by the mistakes of others should be compensated.
Infobesity is not only a challenge for us when it comes to access and select information but I will argue it will also be a challenge for AI systems. The more information we have the more time it will take to process and present the information in a relevant way. The future challenge will certainly be selecting and rejecting information for our purposes.
But the Achilles Heel of information management systems, be they human or machines, is the absence of information rather than abundance of information.
1 “Infobesity: The enemy of good decisions”
Paul Rogers, Rudy Puryear and James Root
Bain and Company
https://www.bain.com/insights/infobesity-the-enemy-of-good-decisions
Best and take care
Lawrence
telephone/WhatsApp: 606081813
Email: philomadrid@gmail.com
http://www.philomadrid.com
PhiloMadrid Skype meeting: WEDNESDAY 31st May: The problem of infobesity
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