84
4 Google as God?
may fundamentally change the system and its properties. If we wanted to change this,
we would have to forbid innovations, but then our world would become as boring as
a graveyard, and could not adjust to environmental, social and technological change
that is happening.
I believe, we could also not be interested in creating an information infrastructure
that creates a broadband information exchange between all brains in the world, or in
creating a computer having the computational capacity of all brains. Why? Because
it would create strongly coupled networks of networks, which would be highly prone
to showing undesirable cascading effects. Harmful mass psychology, as it occurred
in many totalitarian regimes, riots, and revolutions are some examples illustrating the
danger of too much connectivity between people’s minds. As I pointed out before,
many of our anthropogenic systems are vulnerable to cascading effects already, which
often makes them uncontrollable. Privacy may be seen as a mechanism to avoid such
undesirable socio-psychological cascading effects. Without it, we would probably
be involved in many more conflicts.
References
1. C. Song, Z. Qu, N. Blumm, and A.-L. Barabasi, Limits of predictability in human mobility,
Science 327, 1018–1021 (2010).
2. M. Kosinski, D. Stillwell, and T. Graepel, Private traits and attributes are predictable from
digital records of human behavior, Proceedings of the National Academy of Sciences of the
USA 110, 5802–5805 (2013).
3. A.D.I. Kramer, J.E. Guillory, and J.T. Hancock, Experimental evidence of massive-scale
emotional contagion through social networks. Proceedings of the National Academy of
Sciences of the United States of America 111, 8788–8790.
4. J. Schmieder, Mit einem Bein im Knast — Mein Versuch, ein Jahr lang gesetzestreu zu leben
(Bertelsmann, 2013).
5. R.H. Thaler and C.R. Sunstein, Nudge: Improving Decisions About Health, Wealth, and
Happiness (Penguin, New York, 2008).
6. R.M. Bond et al., A 61-million-person experiment in social influence and political mobilization,
Nature 489, 295–298 (2012).
7. D. Lazer, R. Kennedy, G. King, and A. Vespignani, The parable of Google Flu: Traps in Big
Data analytics. Science 343, 1203–1205 (2014).
8. M. Gill, A. Spriggs: Assessing the impact of CCTV. Home Office Research, Development
and Statistics Directorate (2005), https://www.newscientist.com/article/dn26801-mass-survei
llance-not-effective-for-finding-terrorists/.
9. D. Helbing (2015) Thinking Ahead (Springer, Berlin), pp. 181.
10. D. Helbing, The world after Big Data: What the digital revolution means for us, see http://fut
urict.blogspot.mx/2014/05/the-world-after-big-data-what-digital.html.
11. I. Kondor et al. Strong random correlations in networks of heterogeneous agents, J. Econ.
Interact. Coord. 9, 203–232 (2014)
12. C. Hidalgo et al. (2007) The product space conditions the development of nations. Science 317,
482–487.
13. A. Mazloumian et al. (2012) Global multi-level analysis of the ‘scientific food web’, Scientific
Reports 3: 1167.
14. M. Mäs and D. Helbing (2017) Random deviations improve micro-macro predictions: An
empirical test. Sociological Methods & Research 49(2), 387–417, https://journals.sagepub.
com/doi/pdf/10.1177/0049124117729708. Title of preprint: “Noise in behavioral models can
improve macro-predictions when micro-theories fail”.
4 Google as God?
may fundamentally change the system and its properties. If we wanted to change this,
we would have to forbid innovations, but then our world would become as boring as
a graveyard, and could not adjust to environmental, social and technological change
that is happening.
I believe, we could also not be interested in creating an information infrastructure
that creates a broadband information exchange between all brains in the world, or in
creating a computer having the computational capacity of all brains. Why? Because
it would create strongly coupled networks of networks, which would be highly prone
to showing undesirable cascading effects. Harmful mass psychology, as it occurred
in many totalitarian regimes, riots, and revolutions are some examples illustrating the
danger of too much connectivity between people’s minds. As I pointed out before,
many of our anthropogenic systems are vulnerable to cascading effects already, which
often makes them uncontrollable. Privacy may be seen as a mechanism to avoid such
undesirable socio-psychological cascading effects. Without it, we would probably
be involved in many more conflicts.
References
1. C. Song, Z. Qu, N. Blumm, and A.-L. Barabasi, Limits of predictability in human mobility,
Science 327, 1018–1021 (2010).
2. M. Kosinski, D. Stillwell, and T. Graepel, Private traits and attributes are predictable from
digital records of human behavior, Proceedings of the National Academy of Sciences of the
USA 110, 5802–5805 (2013).
3. A.D.I. Kramer, J.E. Guillory, and J.T. Hancock, Experimental evidence of massive-scale
emotional contagion through social networks. Proceedings of the National Academy of
Sciences of the United States of America 111, 8788–8790.
4. J. Schmieder, Mit einem Bein im Knast — Mein Versuch, ein Jahr lang gesetzestreu zu leben
(Bertelsmann, 2013).
5. R.H. Thaler and C.R. Sunstein, Nudge: Improving Decisions About Health, Wealth, and
Happiness (Penguin, New York, 2008).
6. R.M. Bond et al., A 61-million-person experiment in social influence and political mobilization,
Nature 489, 295–298 (2012).
7. D. Lazer, R. Kennedy, G. King, and A. Vespignani, The parable of Google Flu: Traps in Big
Data analytics. Science 343, 1203–1205 (2014).
8. M. Gill, A. Spriggs: Assessing the impact of CCTV. Home Office Research, Development
and Statistics Directorate (2005), https://www.newscientist.com/article/dn26801-mass-survei
llance-not-effective-for-finding-terrorists/.
9. D. Helbing (2015) Thinking Ahead (Springer, Berlin), pp. 181.
10. D. Helbing, The world after Big Data: What the digital revolution means for us, see http://fut
urict.blogspot.mx/2014/05/the-world-after-big-data-what-digital.html.
11. I. Kondor et al. Strong random correlations in networks of heterogeneous agents, J. Econ.
Interact. Coord. 9, 203–232 (2014)
12. C. Hidalgo et al. (2007) The product space conditions the development of nations. Science 317,
482–487.
13. A. Mazloumian et al. (2012) Global multi-level analysis of the ‘scientific food web’, Scientific
Reports 3: 1167.
14. M. Mäs and D. Helbing (2017) Random deviations improve micro-macro predictions: An
empirical test. Sociological Methods & Research 49(2), 387–417, https://journals.sagepub.
com/doi/pdf/10.1177/0049124117729708. Title of preprint: “Noise in behavioral models can
improve macro-predictions when micro-theories fail”.