200
10 The Economy 4.0
had three pillars of knowledge creation, namely theoretical analyses, experiments,
and computer simulations. But the analysis of Big Data now provides a fourth pillar.
Big Data is not an oracle which will answer all the world’s questions, but the
availability of huge data sets will empower us to gain insights in a way that was
impossible before. The analysis of Big Data helps us to find initial evidence quickly,
even though the correlations and patterns discovered by this kind of analysis will often
not imply reliable conclusions. Nevertheless, if combined with good theory, computer
simulations, and/or targeted experiments to verify or falsify certain hypotheses, Big
Data can help us to generate better knowledge faster and more effectively than ever
before. For this reason, Big Data will certainly transform research and innovation.
The health system is another institution which will benefit a lot from Big Data.
For example, IBM’s Watson computer will soon support doctors in diagnosing and
treating diseases by evaluating a much larger body of medical literature and evidence
than doctors could do on their own. In addition, it will become possible to correlate
our health status (or diseases) with our diet, genetic predisposition, and data about
our socio-economic environment. Rather than having to undergo general medical
treatments with considerable side effects, as was the case with antibiotics and other
medication in the past, the health systems of the future will enable personalized
medicine and treatments which will be designed and calibrated to meet the needs of
individuals. These treatments will be more effective while reducing undesirable side
effects: what is good for one person might be bad for someone else. Furthermore,
we might be able to diagnose emerging diseases early on, before they break out,
thereby helping us to prevent them. As a result, disease prevention might become
more important than treatment. Obviously, this will cause a major paradigm shift in
the health system.
A further interesting opportunity is opened up by a recent study conducted by
Olivia Woolley Meza, Dirk Brockmann and myself.
3 To fight pandemics, it is important to immunize people in order to reduce the spread of an infection from one person
to another. But how can we ensure that a sufficient number of people gets immunized (particularly when supply is limited)? Immunizing everyone is typically not
possible because there are usually not enough immunization doses. Informing the
public about the infection through mass media is also not effective because many
people will either not respond or overreact. Surprisingly, however, if people knew
about the number of infections in their social circle, this would let those who are
most likely to be infected seek immunization. In other words, local information can
be more effective than global information. Information platforms such as Flu Near
You or Influenzanet
4 are now making this type of local information flow possible.
To benefit from the opportunities mentioned above, we must carefully establish
a trustful relationship with the patient. Before sensitive personal and health data can
be used, trustworthy and reliable information technologies and governance frameworks need to be developed so that patients have a sufficient level of control over
the use of their treatment and data and how this affects their lives. Most likely, the
3 Woolley-Meza et al. [1].
4 See https://flunearyou.org/ and http://influenzanet.info.
10 The Economy 4.0
had three pillars of knowledge creation, namely theoretical analyses, experiments,
and computer simulations. But the analysis of Big Data now provides a fourth pillar.
Big Data is not an oracle which will answer all the world’s questions, but the
availability of huge data sets will empower us to gain insights in a way that was
impossible before. The analysis of Big Data helps us to find initial evidence quickly,
even though the correlations and patterns discovered by this kind of analysis will often
not imply reliable conclusions. Nevertheless, if combined with good theory, computer
simulations, and/or targeted experiments to verify or falsify certain hypotheses, Big
Data can help us to generate better knowledge faster and more effectively than ever
before. For this reason, Big Data will certainly transform research and innovation.
The health system is another institution which will benefit a lot from Big Data.
For example, IBM’s Watson computer will soon support doctors in diagnosing and
treating diseases by evaluating a much larger body of medical literature and evidence
than doctors could do on their own. In addition, it will become possible to correlate
our health status (or diseases) with our diet, genetic predisposition, and data about
our socio-economic environment. Rather than having to undergo general medical
treatments with considerable side effects, as was the case with antibiotics and other
medication in the past, the health systems of the future will enable personalized
medicine and treatments which will be designed and calibrated to meet the needs of
individuals. These treatments will be more effective while reducing undesirable side
effects: what is good for one person might be bad for someone else. Furthermore,
we might be able to diagnose emerging diseases early on, before they break out,
thereby helping us to prevent them. As a result, disease prevention might become
more important than treatment. Obviously, this will cause a major paradigm shift in
the health system.
A further interesting opportunity is opened up by a recent study conducted by
Olivia Woolley Meza, Dirk Brockmann and myself.
3 To fight pandemics, it is important to immunize people in order to reduce the spread of an infection from one person
to another. But how can we ensure that a sufficient number of people gets immunized (particularly when supply is limited)? Immunizing everyone is typically not
possible because there are usually not enough immunization doses. Informing the
public about the infection through mass media is also not effective because many
people will either not respond or overreact. Surprisingly, however, if people knew
about the number of infections in their social circle, this would let those who are
most likely to be infected seek immunization. In other words, local information can
be more effective than global information. Information platforms such as Flu Near
You or Influenzanet
4 are now making this type of local information flow possible.
To benefit from the opportunities mentioned above, we must carefully establish
a trustful relationship with the patient. Before sensitive personal and health data can
be used, trustworthy and reliable information technologies and governance frameworks need to be developed so that patients have a sufficient level of control over
the use of their treatment and data and how this affects their lives. Most likely, the
3 Woolley-Meza et al. [1].
4 See https://flunearyou.org/ and http://influenzanet.info.