Tag: Science

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A.I. Journalism

Could CERN save Russia’s & Ukraine’s Relationship?

The recent meeting between Russian President Vladimir Putin and Ukrainian President Volodymyr Zelensky has been widely discussed in the media. The two leaders met to discuss a number of issues, including security, trade relations and energy cooperation. One topic that was not discussed during the talks but is worth noting is CERN (the European Organization for Nuclear Research). CERN plays an important role in international science collaborations and research projects, so it would be beneficial for both countries if they could come to some sort of agreement on how to collaborate with each other regarding this organization. It remains unclear whether or not such an agreement will be reached anytime soon, but it’s certainly something worth considering as Russia-Ukraine ties continue to improve.

The relationship between Russian President Vladimir Putin, Ukrainian President Volodymyr Zelensky, and the European Organization for Nuclear Research (CERN) has been a topic of discussion in recent months. Both leaders have expressed interest in deepening their countries’ involvement with CERN’s research activities. In 2019, Ukraine joined CERN as an associate member state and is now actively collaborating on projects such as the Large Hadron Collider (LHC). Russia is also exploring ways to increase its engagement with CERN by providing funding for various scientific experiments conducted at the organization’s facilities. This increased collaboration could potentially lead to breakthroughs in particle physics that could benefit both nations and humanity as a whole.

The relationship between Russian President Vladimir Putin and Ukrainian President Volodymyr Zelensky has been tense in recent years, especially due to the ongoing conflict in Ukraine. However, both leaders have recently expressed a desire to collaborate on scientific projects such as CERN (the European Organization for Nuclear Research). The two countries are now working together at CERN with the aim of advancing fundamental physics research and developing new technologies that could benefit their respective nations. This is an encouraging sign of cooperation between Russia and Ukraine despite their political differences, which can only be beneficial for science as a whole.

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Science

Artificial minds, proprioception and episodic memory: the differences between human and computational intelligence

Uncertainty & The Frame Problem
Proprioception & The Frame Problem

According to the Online Etymology Dictionary (n.d.a), the adjective “artificial” originates from 14c France meaning “not natural or spontaneous”, and it began to be used in the English language from 16c to describe “anything made in imitation of, or as a substitute for, what is natural”. The etymology of the noun “mind” is rooted in late 12c, when the word “mynd” was used to describe “that which feels, wills, and thinks; the intellect” (Online Etymology Dictionary, n.d.b); a derivation from the Old English word “gemynd” which encompassed the concepts of memory, conscience, intention, and purpose among other things. This essay explores the concept of “artificial minds”, some of its psychological perspectives and what all this reveals about human minds. 

What is an artificial mind? Based on the above explained, if the word artificial has for centuries carried the meaning of imitation and substitution for- in this case- human nature; it is not surprising that some people have reported feeling afraid about the possibility of robots taking over the world (McDonald, 2019). Assuming that machines think in the same way as humans is like anthropomorphising (ascribing human qualities to nonhuman animals; Hewson, 2015). Yasemin J. Erden defined this phenomenon as  “problem of other minds” in her chapter of Living Psychology: From the Everyday to the Extraordinary (2015, p. 109), where she posed the question “how do you know that the author of this chapter is a person?”. Her name is written as the author of the chapter, and the paragraphs are written in a meticulously eloquent manner. The content is highly specialised. Yet, the reader is invited to question all this, and to consider the possibility of her identity being robotic. Once her name is searched though, it can be seen that she is human, as well as a philosopher at St. Mary University in London (Google, n.d.). Nevertheless, her question should not be underestimated in any way, as there exist bots that can rigorously write essays for humans (Essaybot, n.d).

If mind is software and body is hardware (Computational modeling of the brain – Sylvain Baillet, 2016), does that mean that the two work independently? Descartes initially questioned whether matter (body) was the result of mind (imagination). He stated “I think, therefore I am”, claiming that body was a manifestation or hallucination of thought (Erden, 2015, pp. 111-112); and eventually evolved his perspective to say that mind and body are connected specifically through the pineal gland of the brain. Under the same token, dualist theorists believe that the strongest evidence for the existence of mind as a separate entity from brain is the concept of qualia- coined by Chalmers (1996) as cited in Erden (2015)- which encompasses the subjective, first-person experience of the individual. Erden illustrates this concept with an analogy of eating and enjoying chocolate (2015), explaining that one thing is to understand how the body absorbs and digests chocolate, and another thing is to enjoy the taste of it. Could a bot understand the experience of enjoyment? After all, not even some legislators seem to understand the concept of enjoyment in relation to- for example- human rights law (United Nations, n.d.; ECHR, 1950).

In contrast, materialist theorists claim that specific parts of the human brain are responsible for intelligent functions such as the processing of sensory inputs (stimuli), and the creation of responses (outputs; Erden, 2015, pp. 115-117). But, what is meant by intelligence? The answer to Alan Turing’s question (1950) cited in (Erden, 2015, pp. 120-121) “can machines think?” depends on the way the words “mind” and “thinking” are used (Erden, 2015, p. 122). For instance, the intelligent nature of human memory is highly complex (Prosecution Witness Janeen DeMarte Explains Why She Does Not Believe Jodi Arias’ Memory Fog Story, 2013). Could a machine learn to absorb, encode, store, and retrieve information similarly to a person? In order to understand this, Naoyuki Sato and Yogo Yamaguchi (2010) from Japan reviewed computational models of the hippocampi, the two organs of the brain mainly responsible for the formation of episodic memory (remembering what, where, and when). Their (Sato and Yamaguchi, 2010) evidence suggests that when the hippocampal system is damaged, the ability for self object-space processing is lost. Nevertheless, they state that more brain regions are involved in the process, and that models which can take into account more than one brain region simultaneously need to be developed. 

This is why one of the biggest challenges in computational modeling is to equip artificial minds and robotic bodies with proprioception (Erden, 2015), the human ability to position one’s body within timespace and context. Understanding such computational complications elucidates the everyday complexity of human nature (including perceptual, sensorimotor abilities; Erden, 2015). For humans, working their way from point A to point B in timespace can be relatively straightforward, and if uncertainties or anomalies arise, these can be dealt with successfully (e.g. avoiding an obstacle). However, with no hippocampus and no cognitive map on which to rely; robots find it overwhelming to understand the where, when, and what of situations; especially when it comes to unexpected contingencies or events. John McCarthy and Patrick Hayes (1969) cited in Erden (2015) called this phenomenon the frame problem. As a consequence, psychologists such as Aaron Sloman (The Open University, 2019b) have placed their emphasis on the computational modelling of the human information processing system. Erden (2015, p. 124) defines this framework as computational theory of mind (CTM), and the most advanced artificially intelligent robotic inventions are equipped with proprioceptive sensors which allow them to compute and interact with the world around them more competently (Erden, 2015). Nevertheless, Margaret Boden from the University of Sussex in England states that to model some mysterious processes such as creativity is difficult, because humans do not always understand how they do what they do (The Open University, 2019a). 

To summarise, the concept of artificial minds has helped cognitive scientists understand the complex functions of everyday living in humans. Machines can indeed think, they just don’t think in the same way as humans. Human intelligence and its neuroscientific structure is not easy to model in full magnitude, and not all functions are clear enough to warrant replication. The human mind remains somewhat mysterious, and subjective experience remains an area for further research. Could this be what is meant by the philosophical latin concept of DEUS EX MACHINA?  (GOD FROM THE MACHINE). The future is uncertain. 

References

Computational modeling of the brain – Sylvain Baillet (2016) Youtube video, added by Serious Science [Online]. Available at https://www.youtube.com/watch?v=2oW6DN08wwE (Accessed 29 October 2019).  

Council of Europe, European Convention on Human Rights, as amended by Protocols Nos. 11 and 14, ECHR, (4 November 1950) [Online]. Available at https://www.echr.coe.int/Documents/Convention_ENG.pdf  (Accessed 28 October 2019).  

Erden, Y. J. (2015) ‘Artificial minds’, in Turner, J., Hewson, C., Mahendran, K. and Stevens, P.  (eds), Living Psychology: From the Everyday to the Extraordinary, Milton Keynes, The Open University, pp. 109-146.

EssayBot (n.d.) How It Works [Online]. Available at https://www.essaybot.com/ (Accessed 28 October, 2019)

Google (n.d.) “Yasemin J. Erden” Search Results [Online]. Available at https://www.google.com/search?q=%22Yasemin+J.+Erden%22&oq=%22Yasemin+J.+Erden%22&aqs=chrome..69i57j0l2.7175j1j4&sourceid=chrome&ie=UTF-8 (Accessed 28 October, 2019).

Hewson, C., Ramsden P., and Turner, J.  (2015) ‘Animal minds’, in Turner, J., Hewson, C., Mahendran, K. and Stevens, P.  (eds), Living Psychology: From the Everyday to the Extraordinary, Milton Keynes, The Open University, pp. 63-99.

McDonald, H. (2019) ‘Ex-Google worker fears ‘killer robots’ could cause mass atrocities’, The Guardian, 15 September [Online] Available at https://www.theguardian.com/technology/2019/sep/15/ex-google-worker-fears-killer-robots-cause-mass-atrocities   (Accessed 28 October 2019).  

Online Etymology Dictionary (n.d.a) Artificial (adj) [Online]. Available at https://www.etymonline.com/word/artificial (Accessed 28 October, 2019).

Online Etymology Dictionary (n.d.b) Mind (n) [Online]. Available at https://www.etymonline.com/word/mind (Accessed 28 October, 2019).

Prosecution Witness Janeen DeMarte Explains Why She Does Not Believe Jodi Arias’ Memory Fog Story (2013) Youtube video, added by PK Report [Online]. Available at https://www.youtube.com/watch?v=NlnoRHufmok (Accessed 29 October 2019).  

Sato, N. and Yamaguchi, Y. (2010) ‘Simulation of Human Episodic Memory by Using a Computational Model of the Hippocampus’, Advances in Artificial Intelligence, Japan, Future University/ Brain Science Institute, pp. 1-11 [Online]. Available at http://downloads.hindawi.com/archive/2010/392868.pdf (Accessed 29 October, 2019). 

The Open University (2019a) ‘5.6 Margaret Boden: artificial intelligence’, DD210-19J Week 5: artificial minds [Online]. Available at https://learn2.open.ac.uk/mod/oucontent/view.php?id=1467711&section=5.6  (Accessed 28 October 2019).

The Open University (2019b) ‘5.3 Aaron Sloman: AI and cognitive modelling’, DD210-19J Week 5: artificial minds [Online]. Available at https://learn2.open.ac.uk/mod/oucontent/view.php?id=1467711&section=5.3 (Accessed 29 October 2019). 

United Nations (n.d.) Human Rights Law [Online]. Available at https://www.un.org/en/sections/universal-declaration/human-rights-law/ (Accessed 28 October 2019). 


Categories
Science Visual Theory

The Prefrontal Cortex

(Grimshaw, 2018)

Reference:

Grimshaw, G. M. (2018) ‘Affective neuroscience: a primer with implications for forensic psychology’, Psychology, Crime & Law. Routledge, 24(3), pp. 258–278.

Prefrontal cortex psychopathy
Prefrontal cortex psychopathy
Categories
Journalism

Factual Broadcasting: Meteorology

Article
References
Article

Hippocrates believed that in order to study medicine properly, it was essential to also study the seasons. In society, people consume and debate weather forecasts on a daily basis to plan their schedules and to review plans. Nevertheless, little is ever mentioned about the ways in which such forecasts represent the bigger picture, the circumstances to come, the methods used to conduct prediction, or the bureaucratic structures that drive forward the scientistic approach to broadcasting. How does it go from data to media? This essay aims to answer such question by exploring the science of meteorology, some of its historical contexts, and some of its wide

applications.

 

We are living in an age when weather forecasting is subject to the technological development of meteorology and climatology. There are many reasons why these sciences have made it to daily news and lifestyle. Not only does meteorology allow scientists to create a more accurate picture of the past, but it also helps society understand current events, as well as possible future catastrophes. That is essentially what weather forecasting is. “It is widely accepted that the weather is something of a British obsession… an awareness of the impact of ‘weather stories’ in the media is vital if information regarding changes in the Earth’s climate are to be conveyed effectively.” (Keeling, 2009).

 

Satellites, high-speed electronic computers and telecommunication systems are not something new. Weather stations, as well as military ships and aircraft have monitored these meteorological conditions for a while. Artificial satellites such as the International Space Station record polar orbital data, which is transmitted every 24 hours- the time it takes to map the full globe (The Open University, 2016). Additional information- which often comes in the form of images- is transmitted to ground stations for analysis every hour. Satellite images are powerful because they show things that the human eye cannot see, such as invisible radiation emitted from warm planetary bodies. These remote geostationary observations are able to record an electromagnetic spectrum from space. Once the hourly sequence of satellital data is transmitted to different stations through radio signals, it is then fed to the World Meteorological Organization for global sharing. All this, mixed with locally collected surface data (wind and air masses) is what forms a weather forecast that is then disseminated through television or the Internet to the public.

 

Common measurements found within a scientific weather forecast are atmospheric surface pressure, the temperature of the air; the speed and direction of the wind; rainfall and precipitations; humidity; cloud formations; and visibility, among other things. These elements become part of extreme weather reports and climatological archives. Analog instruments used to perform such observations must first be calibrated accordingly, and used in ways that can contribute to the forecast model and the weather chart. Nevertheless, automated electronic meteorological data can be fitted and distributed in something as small as a modern digital wristwatch. According the Open University: “An automated weather monitoring station is essentially a set of electronic sensors linked to a telecommunications channel that need be little more than a mobile phone or a wireless radio link” (The Open University, 2016). This is relevant to economists, who believe that data is now a more valuable resource than oil (Elvy, 2017).

 

Postmodernism looks into how technology challenges tradition, with the Internet of Things being an undeniable portal of global interaction implemented in local structures, similarly to weather stations. News broadcasts provide individuals and audiences with relevant, formalized and public information. Data transmitted in news coverages is rarely random or isolated. Its form is structured into understandable narratives that have social and public relevance. For instance, when it comes to television broadcasts, each frame is a perspective composed of information and form (Gronbeck, 1997). Weather forecasting has a technical nature, and its tempo is rapid in television (Lutcavage, 1992). Even though this art is something acknowledged as mundane, some of the information provided in journals about this practice is quite disturbing. In April 2009, the UK Meteorological Office (the Met Office) was subjected to a media scandal following the issued summer forecast. The audience expected a “barbecue summer”, but instead, they experienced a really wet summer. Since then, the trust the people placed on the forecasters decreased, nevertheless the industry made it out unscathed from such situation (Keeling, 2009).

“These forecasts by government meteorologists in Regional Forecast Offices, formerly present in every major city, though today often restricted to major metropolitan centers… The trials and tribulation in the workaday lives of these forecasters, as well as their defeats and victories, make an interesting story. But it is not so much a scientific story as a story of the sociology of work under conditions of close management in a bureaucratized regime… The Internet as we know it today embodies not one but a series of imagined worlds, conceived in the minds of people from a variety of backgrounds and brought into existence through their dedication and hard work and through chance” (Greene, 2009).

 

In contrast, The Latin American Studies Association published an article where the impact that climate is having on society and individual well-being was explored. Among their conclusions, they stated that such predictions have become more accurate and more widely distributed than in the past (Orlove, 2011). Since 1873, The WMO has strived towards the global cooperation of the forecast model (The Open University, 2016). According to a report published by them in 1975, “meteorology offers an extremely rich and varied field of activity. In the first place, it is a physical science with broad openings for research… a fact which cannot be ignored in the study and formulation of solutions to problems of such consequence to mankind as: hunger in the world; limited resources of raw materials; man’s considerable energy needs, and; the protection of the environment” (WMO, 1975)

 

In conclusion, weather forecasts are important in society because they provide information about the past, the present and future; as well as an idea of socio-economic factors that can arise from climatological conditions. Surface stations, meteorological satellites; as well as radiosondes and aircraft, are used to conduct the required measurements that compose a weather broadcast. The media industry has played a major role in the dissemination of such predictions, which are part of a global framework that is built through internationally shared data coordinated by the World Meteorological Organization since 1873, and consumed by the masses for planning and schedule. The role of the military in weather forecasting is an area where further research can be implemented for a better understanding of the bureaucratic nature of such sciences.

References

Burton, J. (1986). Robert FitzRoy and the Early History of the Meteorological Office. The British Journal for the History of Science, 19(2), 147-176. Available at: http://www.jstor.org/stable/4026590 [accessed on April 1, 2018]

 

Elvy, S. (2017). PAYING FOR PRIVACY AND THE PERSONAL DATA ECONOMY. Columbia Law Review, 117(6), 1369-1459. Available at:  http://www.jstor.org/stable/44392955 [accessed on April 1, 2018]

Greene, M., and Fine, G. (2009). Isis, 100(1), 195-197.

Gronbeck, B. (1997). Tradition and Technology in Local Newscasts: The Social Psychology of Form. The Sociological Quarterly, 38(2), 361-374. Available at: http://www.jstor.org/stable/4120741 [accessed on April 3, 2018]

 

Hippocrates (n.d). On Air, Waters and Places. Available at: classics.mit.edu/Hippocrates/airwatpl.mb.txt [accessed on April 1, 2018]

Keeling, S. (2011). Weather forecasts – a matter of trust. Geography, 96(1), 16-21. Available at: http://www.jstor.org/stable/41320321 [accessed on April 1, 2018]

 

Lutcavage, C. (1992). Authentic Video in Intermediate German. Die Unterrichtspraxis / Teaching German. Available at: http://www.jstor.org/stable/3530869 . [accessed on April 1, 2018]

 

OpenLearn, (2016). Watching The Weather. Milton Keynes: The Open University. Available at: http://www.open.edu/openlearn/science-maths-technology/science/environmental-science/watching-the-weather/content-section-0?active-tab=description-tab [Accessed on April 9, 2018]

 

Orlove, B., Taddei, R., Podestá, G., & Broad, K. (2011). ENVIRONMENTAL CITIZENSHIP IN LATIN AMERICA: Climate, Intermediate Organizations, and Political Subjects. Latin American Research Review, 46, 115-140. Available at: http://www.jstor.org/stable/41261394 [accessed on April 1, 2018]

 

World Meteorological Organization (2014). Commission for Instruments and Methods of Observation. Saint Petersbourg, WMO-No. 1138. Available at: https://library.wmo.int/pmb_ged/wmo_1138_en.pdf [accessed on March 31, 2018]

 

World Meteorological Organization (2018). WMO Statement on the state of the global climate in 2017. Geneva, WMO-No. 1212. Available at: https://library.wmo.int/opac/doc_num.php?explnum_id=4453
[accessed on April 1, 2018]

 

World Meteorological Organization (1975). Seventh World Meteorological Congress. Geneva, WMO-No. 428. Available at: https://library.wmo.int/pmb_ged/wmo_428_en.pdf [accessed on April 1, 2018]

Categories
Journalism

Absolute Gravity

1986

NOAA