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History of Artificial Intelligence within Computer Science

Oxford Languages defines artificial intelligence (AI) as 'the theory and development of computer systems able to perform tasks normally requiring human intelligence'

The Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI), held in 1956, saw the emergence of AI as a discipline. It was here where John McCarthy, who first coined the term 'artificial intelligence', met with other academics such as Marvin Minsky, Nathaniel Rochester, and Claude Shannon to research and discuss AI.

Before its establishment as a discipline, AI was a popular subject amongst researchers. Perhaps the most notable work being the Logic Theorist, a computer program created by Allen Newell, Herbert A. Simon and Cliff Shaw in 1955, which was later presented at the DSRPAI.

Significant Work

Alan Turing was a British mathematician and computer scientist who famously cracked the enigma code during WW2, reaching feats in the field of AI before its debut. In his 1950 paper, 'Computing Machinery and Intelligence', he details the Turing test which sought to answer the question "Can Machines Think?". Turing describes 'The Imitation Game' in which an examiner questions a computer and a human to identify one from the other. Based on Turing's work, the CAPTCHA is now more widely used to determine whether a user is a computer or a human.

At the MIT Artificial Intelligence Laboratory, Joseph Weizenbaum developed ELIZA - a natural language processing computer program - released in 1966. Many users thought ELIZA could conceptualise but she was simply "pattern matching". Despite this, ELIZA was one of the first programs with the capability to attempt the Turing test.

In 1997, the reigning chess champion Garry Kasparov was defeated in multiple chess matches by IBM's supercomputer Deep Blue. Of the six games, three were a draw, one a win for Kasparov, and two were won by Deep Blue.

Education and the Future of AI

At higher education, artificial intelligence is primarily taught as part of a computer science degree but is now increasingly being offered as a standalone course. AI has roots in many subject areas including philosophy, mathematics, psychology, and biology. Within psychology, for example, to build artificially intelligent machines requires an understanding of how human brains function. Its versatility as a discipline is reflected in the multiple sub-fields of AI - neural networks, robotics, speech processing, machine learning, etc.

With AI expanding as a discipline, the AI worldwide software market grows year-on-year (approximately 54% from 2019-20). However, there are concerns about AI and what it means for our future. Often these are centred around unemployment, security, inequality, and singularity. These concerns point to a different direction for AI; one which interests the public sector.

Evidence in Aggression

The most widely used definition of aggression is 'any act that harms another individual who is motivated to avoid such harm'. Importantly, aggression refers to behaviour that is intended to hurt another living being, physically or verbally, and this can be direct or indirect. Evidence in aggression consists mostly of correlational studies and laboratory studies.

Biological Evidence

Genetic Factors

MAOA-L is a variant of the monoamine oxidase A (MAOA) gene which causes low MAOA activity and has been linked to increased levels of aggression. The MAOA gene governs the production of the MAOA enzyme which deconstructs neurotransmitters to be reused. Evidence of this correlation includes a study of an extremely violent Dutch family, convicted of rape and attempted murder, which found unusually low MAOA activity in their brains.

Isolating genetic factors has been a challenge for researchers. The difficulty lies within separating genetic and environmental factors. Frazzetto et al. provide evidence for the interaction between these factors - within his sample, only participants who had experienced significant trauma in early life demonstrated a correlation between MAOA-L activity and high levels of aggression. This gene-environment (GxE) interaction is often referred to as diathesis-stress.

As there is no standardisation when measuring aggression, researchers use a range of methods including self-reports, teacher and parent reports, and direct observations. This can prove problematic when results differ based on the method used. In a meta-analysis of 51 twin and adoption studies by Rhee and Waldman, genetic factors were found to have a greater effect on aggression in studies that used self-reports rather than teacher or parent reports.

Social Psychological Evidence

The social learning theory

Bandura observed that aggression can be learnt directly, through operant conditioning, and indirectly, through observational learning. He describes vicarious reinforcement - a child is reinforced to behave aggressively if they see it work effectively for their models i.e. aggressive behaviour results in desirable consequences. Bandura's famous Bobo doll study supports this hypothesis. In his study, children individually watched an adult model behaving aggressively towards a 'Bobo doll'. To create frustration, the participants weren't allowed to play with other toys between their observation time and their time with the 'Bobo doll'. Results show the children mirrored the aggressive behaviour they had seen earlier, without being provoked. In another group, of children observing a non-aggressive model, hardly any aggressive behaviour was shown towards the 'Bobo doll'.

Cultural differences mean that in certain cultures, like !Kung San in the Kalahari desert, social norms don't permit aggression so aggressive behaviour isn't reinforced directly or indirectly. Without the presence of a model, children still displayed aggressive behaviour. This perhaps suggests there is an instinctive element to aggression that a biological approach might better explain or that the social learning theory can only be applied to western cultures as the theory would struggle to interpret this specific finding.

Media Influences on Aggression

The effects of computer games

Evidence for the effects of computer games on aggression includes laboratory experiments, correlational studies and longitudinal studies. Anderson et al. completed a meta-analysis of this evidence and found a correlation between exposure to violent computer games and aggressive behaviour. These results were present in both sexes and across individualist and collectivist cultures.

A correlation, however, is not causation i.e. exposure to violent computer games and aggressive behaviour can be closely associated but this doesn't mean that one causes the other, nor does it indicate the direction of causality. It is also possible that a third variable, a confounder, is responsible for aggressive behaviour which a correlation doesn't consider as it only studies two variables.

Truth in Cartography

Cartography is the 'discipline dealing with the art, science and technology of making and using maps'. Cartographers start by collecting data from the featured area so they can detect patterns to present. They try to depict this data accurately on a map which is then given to a map user to interpret. Users change the map accordingly and create a final projection. The cartographic process is lengthy and one which involves many components from different disciplines.

Persuasive Cartography

Persuasive cartography describes maps intended to influence opinions rather than display impartial geographic information. There are many factors which affect how a map is perceived, including text, colours, projections, shading, and images. As cartographers make decisions about these factors, few maps display a completely objective view of reality. They can have this influence on opinions and beliefs because most people assume maps are objective and true, made by professionals who would never purposely misinform.

A common example of distortion is the Mercator projection. While this projection is useful for navigation, it has often been criticised for misrepresenting sizes - specifically diminishing areas close to the equator and enlarging world powers. Canada and Russia, for instance, seem to make up about 25% of the Earth's landmass when actually they only hold 5%. Another discrepancy, brought to the world's attention by the computer-graphics designer Kai Krause, is 'The True Size of Africa'. The map aims to 'fight against rampant Immapancy' by showing several countries packed into Africa's outline. The term 'Mercator Effect' has since been coined, which refers to the alleged effect this projection has on our cognitive map of people. A more accurate depiction of landmasses, the Gall-Peters projection, is now increasingly being used.

This phenomenon also applies to political maps, namely the political map of India. Published in 2015 by the country's official survey office, the map includes the disputed regions of Jammu and Kashmir within its territory. While Pakistan does label this region as 'disputed territory' on their map, the colour-coding implies it is under singular control. These maps can significantly affect the beliefs of these countries' citizens, especially as they are endorsed by their governments.

Power in Contemporary International Relations

In international relations, power refers to the capacity to convince another entity to behave in a way they would not have otherwise behaved. Hard power is defined as the ability to influence states via coercion, through military status and economic sanctions. The term 'soft power', first introduced by American political scientist Joseph Nye, describes a state's ability to influence others through persuasion, not coercion. This is possible through the attractiveness of a nation's culture and foreign policy, rather than their economic and military power.

Hard and Soft Power

Hard power is embodied by realism; states can achieve sovereignty through military power within our anarchic international system. It takes a shorter amount of time to acquire hard power, rather than soft power, as its resources are tangible e.g. trade embargos. Its effect, however, is only short-lived as it relies on the pressure states feel to act in a certain way, different from its regular practices. Historically, world powers have been the product of hard power. The US, for example, has acquired much of its status through military action. In 1898, when the Spanish-American War took place, the US acquired Puerto Rico, Guam and the Philippines through military means. Since then, the US has continued to expand, with heavy involvement in global affairs. Currently, they have around 800 military bases across the world, a threat many countries cannot ignore.

Contrastingly, soft power relies on culture, political values, institutions, and legitimate practices. Legitimacy is central to soft power - to exercise soft power, a state's activities need to be recognised as legitimate. Time is also integral to soft power. As its resources are intangible, it takes a longer amount of time to build soft power, rather than hard power, but its effect is longer-lasting. Now the spotlight is on soft power. Firstly, hard power can be ineffective - when the US invaded Iraq in 2003, they ignored how their actions would be perceived by their allies and the illegitimacy of the attack, which jeopardised global confidence in US leadership. Secondly, in our increasingly digitalized world where the public plays a more active role in international politics, soft power practices are essential.

Looking to the Future: Smart Power

With the ineffectiveness of hard power and the limitations of soft power now recognised, world leaders look to smart power. Smart power is the capacity of a state to integrate aspects of hard power and soft power to advance a state’s goals effectively and efficiently. It involves a balance between strong military and economic tools and secure alliances and institutions. The EU is perhaps one of the best examples of this. The EU possesses military and economic power but ultimately, decide the norms for international relations. Actors are encouraged to comply with these norms to receive its benefits i.e. decades of peace between 27 nations.

Smart power requires smart strategies; those which respond promptly to our ever-changing world. Currently, these strategies should look to address our increased global interconnectedness and the increased development of target populations. With more access to formal education and the availability of social media, countries in Asia, Africa, and Latin America have grown more sophisticated and aware of their own society and less susceptible to the influence of others. These newly educated populations, therefore, require a different approach, smart power.

The Fluctuating Power of Theories

We live in a world which is constantly changing - the explanatory power of a theory in IR will fluctuate according to context. Before the world wars, for example, liberalism had strong explanatory power, namely for its democratic peace theory. The theory states that liberal democracies are less likely to go to war with each other than non-democratic states. Bremer's statistical analysis provides compelling evidence, ‘even after controlling for a large number of factors...democracy’s conflict-reducing effect remains strong’. The commencing of the Cold War, however, triggered disillusionment with this previously dominant theory. The state-centric nature of realism was able to more accurately interpret the actions led by the US and the Soviet Union e.g. the constant replacement of communist-led governments for capitalistic authority. More recently, we have witnessed a rise in power for constructivism, a theory able to explain change in the international system through norms, diffusion, and socialisation. In contrast to realism, leading constructivist Wendt believes, 'Anarchy is what states make of it'. It follows that self-help and sovereignty are norms which have changed our interests and led us to believe we need to defend territorial boundaries.

Human Monogamy in Evolutionary Biology

Male Goeldi's marmosets regularly check their mates' reproductive condition by inspecting her genital scent glands.

As only 3-5% of the mammalian species are socially monogamous, evolutionary biologists deem the prevalence of human monogamy an anomaly. In seeking an explanation, academics have extrapolated ethological work to humans.

Research suggests that ecologically imposed monogamy may originate in early monogamous couples when population levels were low and scarce resources could only provide well for a couple and their offspring. Male and female partnerships thus emerged as the most effective way to utilise resources. This explanation is well-documented amongst biologists; Benshoof and Thornhill indicate that monogamy is mutually beneficial, citing the example of marmoset Callimico goeldii. The female’s reproductive success heavily depends on ‘the food and protection provided by the hunting male’, while the male invests in his relationship to ensure ‘the survival of his young and thus his own reproductive success’.

Whilst this explanation has been contested, the general consensus is that a monogamous mating system is more likely to survive within a population. Cooperative breeding details the differences in kin-based benefits between non-monogamous and monogamous mating systems. As kin-based benefits are diminished under female multiple mating, biologists predict that monogamy is key to increase relatedness within a system and receive the subsequent evolutionary advantages.