546. AI, moral agents and patients

There is talk of Artificial Intelligence (AI), robots, overtaking the human being in intelligence, and dominating it. If that were the case, not to harm us, could robots develop a sense of morality, virtues, to prevent humanity from being overwhelmed? Robots are agents, they act, such as automated soldiers, drones, medical operators. AI includes many things that do not act, but are in boxes and spout results of algorithms.

I follow Damasio (2003) in seeing the human body and mind as a homeostatic system, keeping the physical and mental organism within bounds of viability. Emotions serve to trigger beneficial actions and obstruct harmful actions and influences, contributing to survival. Emotions and intelligence are intertwined in guiding human action (Nussbaum, 2001).

It seems that to be moral, robots would have to be conscious. How would we know if that is the case? We could have something like a ‘Turing test’: if we cannot, in their observed behaviour, distinguish robots without inner morals from those with it, can we not call robots with moral conduct but without corresponding mental states and emotions ‘moral’?

In the development of robots there is a ‘top-down’ approach, in programming rules into robots, and a ‘bottom-up’ approach, of self-learning, robots who develop their own internal structure in interaction with their environment, mimicking evolution. If benevolence and morality with humans arose from their  beneficial effect on group survival in evolution, how could that work for robots? What selection environment could, in an evolutionary process, with robots interacting with each other and humans, be devised for robots to develop benevolence and morality? Could robots not develop, on the contrary, to develop a destructive stance toward humans, seeing them as a threat to their survival? How do we decide on the selection environment conducive to outcomes that are beneficial to humans?  

Someone involved in developing robots said that it would be best to aim at the optimal use of complementary skills of robots and people. That would require some social skills in robots. It will take considerable time for robots to develop such skills. It is predictable that the logic of markets would cause acceptance in the shorter term of cheaper robots without such skills. This would cause an undirected, haphazard, uncertain and risky development of the stance of robots towards people.

Danaher (2019a) presented a different view of robots and the threat they may yield, even if they are benevolent and function very well. He distinguished between ‘moral agents’, who act and take responsibility for the morality of their actions, or the lack of it, and recognise the moral agency of others, and moral ‘patients’, who passively profit from the blessings of technology and the moral beneficence of the morality of others. AI can enable agency but also furthers patiency of people. Agency and patiency are not all or nothing, but more or less of both. There is, however, tendency for people to shift from moral agency to moral patiency. It has been going on for some time, but it accelerates, can reach its pinnacle in the use of robots.

Danaher gives the example of cars, They used to enable agency, in getting us to places, but with gimmicks of GPS, route planning and automated driving they contribute to moral patiency, to the point of leaving care against accidents to the robot. That could, we hope, still enable activities such as sitting in the back of the car and reading a book, but how many people will do that? It contributes to the overall surrender by people of life to robots.

Danaher (2019b) also asked the question whether human can be friends with robots, and answers in the affirmative. He goes back to Aristotle’s view of the dimensions of friendship: mutuality, honesty/authenticity, equality/no dominance, and diversity of interactions, which one can all doubt with respect to robots. However, human-human friendships ae also seldom equal, and do not extend across the full range of human life. If a relationship is does not cover the full range of life, this can be a blessing. Donaher gives the example of contact via internet. That can make the contact shallow but it can also help in avoiding prejudices that hinder direct relationships, such as race, colour, class, education, which fall outside the internet contact.

It is more difficult to assign mutuality and authenticity to robots. Robots may evolve by adapting to circumstances, but what if those circumstances radically change? I agree that robots can still be friends in the sense of yielding benefits and doing pleasurable things together. Danaher quotes the work of Julie Carpenter’s example of bomb disposal squads seeing their robots as friends and even honouring them at funerals when they fall. Robots  can compensate for disabilities, and one can become ‘friends’ with them in the way that a lame person can become friends with its guide dog.

However, though less blatantly than with sex robots, people may turn from human friends to robot friends because they are more obedient and less contrary. That would be disastrous for humanity, since one needs precisely the opposition of the other to develop one’s identity.

On the other hand, with their potential wealth of knowledge robots may act as intermediaries between humans, and Danaher argues that robots can be used to ‘outsource’ activities that form obstacles to human-human friendship. Danaher tells the example where ongoing pressures of one side of the friendship to play tennis may irritate the other and block the friendship, while now one play tennis with the robot. Of course, one can also seek a human friend who likes to tennis, even if that friendship is limited to the joint enjoyment of tennis.

Summing up: robots can be friends even if that is not a ‘deep’ friendship, and they can facilitate human-human friendship.

  

Danaher, M. 2019a, ‘The rise of robots and the crisis of moral patiency’, AI and Society

Danaher, M. 2019b, ‘The philosophical case of robot friendship’, Journal of Post-Human studies.

Damasio, A. 2003, Looking for Spinoza; Joy, sorrow and the feeling brain, Orlando FA: Harcourt

Nussbaum, M. 2001, Upheavals of thought, Cambridge: Cambridge University Press.

  

 545. paradoxical elites

Elites are needed for representative democracy, but can also destroy it. Liberal democracies are a combination of a vertical direction and representation by an elite and a horizontal corrective by citizens. Highly and Burton (2006) claimed that liberal democracies need integrated, consensual elites, that share norms of conduct in political rivalry without violence, with negotiation and collaboration. ‘The sine qua non of liberal democracy is a well-ordered, internally accommodative, and relatively secure political elite’. (see also Schonfeld, 2008). This is as natural as organisations having directors. Direct, unmediated access to the will of the people is an illusion. Populists who militate against elites and claim direct access to the population when in power will themselves institute an elite, while hidden under a euphemism of ‘cadres, officials or functionaries’ (Pakulski, 2012:13).  Highly and Burton  speak of a web of overlapping and interlocked sectoral elites across different layers of society, such as industries, interest groups, social groups and NGO’s .

While a democracy requires such an elite, there are other types of elite that are not conducive to democracy. More often than not, there are ‘disunited elites’ that vie with each other and compete for dominance, often with violence, as used to predominate in Europe in the past, and now predominate in many African countries. The transition to an integrated, consensual elite is possible, but takes time and a certain prosperity in order to stmulate the wish for preservation of the status quo, and mobilisation of non-elite support. Third, there are ideologically united elites, that on the surface agree on a religious or political doctrine, but hide dissent that is carefully masked, as in Iran, Northern Korea, the former Soviet Union and current Russia under Putin, yielding a ‘simulated democracy’. (Pakulski, 2012: 15)

The integrated, consensual elites share social and recreational facilities ‘in executive and priviliged settings ‘ (Highly and Burton, 2006: 11), exhibit reciprocity in maintaining cohesion, preserving their structural unity, in a ‘stable polyarchy’,  and maintain a ertain secrecy of proceedings, a certain amount of protection against  reputational damage under mistakes, and revolving doors of careers between different networks in the web.  They tend to be technocratic, emphasising technical and procedural feasibilities, rather than ultimate rights and wrongs. This is in ganger of yielding the risk of an inward look, myopia and even blindness to some societal needs and opinions. This is easy to condemn, but is an outflow of the neccessary sharing of a morality of conduct. However, elites cannot afford to ignore those needs, and they are disciplined by periodic  elections. Nevertheless, correctives are needed such as an ombudsman or courts of appeal. Social media can give opportunities for direct contact, horizontalisation, between citizens and representatives, bypasssing or influencing representation, but in practice they often derail in invective, vindictiveness and outrageous conspiracy theories.  

Highly J.H. and M. Burton 2006, Elite foundations of liberal democracy, Plowman & Littlefield.

Schonfeld, W.R. 2008, ‘The foundations of liberal democracy’, Contemporary Sociology, 37/3.

Pakulski, J. 2012, ‘John Highly’s work on elite foundations’, Historical Social Researcg, 37/1: 9-20.  

 544.The dilemma of benevolence and justice

 A prominent writer about self and other was Emmanuel Levinas (1991). He proposed that the other and the relation with him/her precedes the ego. ‘The relation is the liberation from the fortification  of the ego’ (Lipari, 2004: 129). He deviated fundamentally from the old idea, going back to Descartes, that the ego, the subject, has a pre-formed identity, and looks at the world, the object, from outside. Levinas objected that this turns the other into an object, to be used as an instrument for the benefit of the  self.

 De original meaning of ‘theory’, in ancient Greek,  was ‘seeing’, which yields ‘comprehension’. Levinas is suspicious concerning such seeing and comprehending, because they press things into pre-conceived moulds of conceptualisation, neglect what is invisible in the object, its background, its history and what lies beyond its horizon, its potential for developing.

 Nevertheless, Levinas speaks of opening up to the ‘visage’ of the other. It seems to be seeing, but does not pass by the idiosyncracy of the other that results in its shrivelling. That other seeing of Levinas precedes  rational categorisation. Levinas calls it a ‘trace’. Perhaps is a good term for the effect of the instinctive benevolence thrown up in evolution, as proposed by David Hume. That yields a potential which may not be realised. It can be smothered in adverse education or harshness in the struggle for life. Levinas himself says he following about it: ‘ it precedes every memory. It is made in an unrecoverable past, which the present, proposed in memory, cannot match, in terms of birth or creation (Levin, 1999: 321).

 For Levinas the other is ‘high’ by the epiphany of its face,  one must care unconditionally for him/her, in an asymmetric relation, where the other takes precedence over the self. The face of the other calls out, which precedes any action, with the imperative to care for him/her, in full dedication. It is not like opening the door of one’s house to the other, but letting him/her participate in building the house. Self and other differ, and cannot merge, and the other must be accepted and valued in its own identity. The letting the other in is unconditional. Levinas says that one must accept even one’s hangman.

 The evolutionarily given, instinctive nature of the trace can perhaps contribute to solving the dilemma that Levinas encounters, and admits, concerning on the one hand the unique individual whose face demands unconditional care, and on the other hand justice, which applies to all equally, brings humanity together, in a categorisation, putting in a box, which Levinas wants to avoid. I call this the ‘dilemma of benevolence’. Benevolence is individual, made to measure, while justice, requires implies equality under the law. This dilemma manifests itself widely. Sometimes inequality is required by benevolence. For example in inequal, progressive taxation, and benefits extended to the indigent and not to the well-to-do. It comes up in the present quarrel, in the Netherlands, to reduce the rising price of fuel and energy as a result of the crisis in Ukraine. Why let higher incomes also benefit from this, rather than focusing on people who are now in financial crisis?    

One cannot craft an arrangement that seamlessly suits individual taste and at the same time is the same for all. Care for every single individual person must make the transition to justice for all, with rules that apply to all and are impersonal. (e.g. Levinas, 1991: 113–15). One must somehow not only feel responsible for that unique other, but also for third parties, and ask oneself whether the unique other does not harm other others. The asymmetry of the ideal relationship vanishes, and equality under the law appears. Yet the Levinassian relation must be preserved as source of inspiration and standard for social justice. How can we ensure that law and justice, with all its institutions and power holders, can remain inspired by the responsibility of the self for the unique other? According to Levinas that is the calling for ‘prophetic voices’ that one hears sometimes, rising from the folds of politics, from the press and in the public spaces  of liberal states (Levinas, 1991: 203). Is that strong enough?

Levin, D.M. 1999, The philosopher’s gaze; Modernity in the shadows of enlightenment, Los Angeles: University of California Press.

Levinas, E.1991, Entre nous, Essais sur le penser-a-l’autre, Paris: Grasset

Lipari, L.2004, ‘Listening for the other: ethical implications of the Buber-Levinas encounter’, Communication Theory, 14/2: 122-41.

 

 

543. Institutional crowding

 The economic principle of diminishing returns says that as you accumulate more of something, say wealth, the utility of an addional unit decreases. You get saturated. An additional dollar can mean survival to a beggar, but means virtually nothing to a millionnaire.

Similar, but concerning the increasing cost of acquiring an additional unit, is the principle of EROI, Energy Return on Investment, applying for example to exploiting a natural resource. It says that as you are take out more, the cost of an additional unit increases, you need to put in increasing energy.

Here, I want to mention another variant, which I call ‘institutional crowding’, which concerns the increasing difficulty and cost of adding a regulation or law to an already large collection of them. It makes me think of a game of blocks I play on my smart phone, where one has to add additional irregular configurations of blocks into a limited space where you already added a number of such configurations. There is less and less fitting space to add an additional one. To proceed, there must also be the possibility of eliminating already added blocks.

The government of a liberal democracy feels pressed, to preserve votes in elections, in competition with especially populist parties, to acommodate needs and desires with new social benefits, subsidies or tax reductions to special interest groups. Also, to make a political career, parliamentarians and members of municipal councils need to profile themselves by initiating ever new regulations. But financial and bureaucratic capacity are limited, and with laws and regulations it is difficult to abolish already existing ones to make room for new regulations, because they are seen as acquired rights that may not be violated.

 This is one of several threats to liberal democracy, which cannot resort to dictates that an authoritarian regime allows itself. I am not pleading for less social security or fewer benevolent regulations, but for regulations that save on bureaucracy and institutional crowding.

A prime example of such regulations is that of a Universal Basic Iincome (UBI), for which I pleaded before, in this blog. Since it is unconditional, applying equally to all, not depending on work or wealth, it is not bothered by boundary conditions, who gets it and who not, which clog up the system and further a mentality of regulatory distrust and control.

Some say that a UBI of, say, some 1000 euros per month per person would cost too much, necessitating too high a tax rate, but this has not been analysed carefully enough. In available calculations, likely positive effects have not been taken into account, such as the impulse it would give to entrepreneurship, since in the risky times of setting up business, one can fall back on the UBI when things go wrong. One can say that taking out he risk of entrepreneurship, will produce more worthless initiatives, but enough risks remain, since the UBI is stil too low to satisfy anyone but the most frugal people, and there is the risk of unsuccessful effort and loss of time. Also, there would be savings in less cost of social arrangements and attendant bureaucracy, though not all existing arrangements can be abolished. One can also think of other taxes than on labour, such as on the use of robots and highest wealth. Tax on the production of robots might chase their production outb of the country, but the robots used in the country cannot flee.         

542. Causality of social systems

 I have used Aristotle’s multiple causality of action in discussions of economics (Nooteboom,  2019) and virtue ethics (in an as yet unpublished article).The causality consists of:

The ‘efficient’cause’: the agent(s), say a carpenter

       ‘material’cause’: the wood the carpenter uses

       ‘formal cause’  : the craft he uses

       ‘final cause’     : his purpose; earning a living, remaining independent, being creative

       ‘conditional cause’: market, competition, institutions

       ‘exemplary cause: design, model

 Aristotle made the error of attributing this causality to nature. Nature, say a falling stone, does not have a final cause. This discredited his causality, which is a pity, since it admirably suits social sciences and economics. Causality came to be seen as mechanical push, or as a mere formal condition of a cause consistently preceding an effect. This yielded the ‘INUS condition’: causes have to be individually necessary and collectively sufficient. There is a prevailing intuition of a linear causal chain. In fact, causes can be, and often are, multiple and simultaneous (MacCumber, 2007). I found Aristotle’s causality very fruitful, and am inspired by it to see what a multiple causality of social systems would look like.

I maintain the efficient, material, formal and conditional causes, with a twist, instead of the final cause I adopt a ‘generative cause’, and I add an ‘institutional cause’, as follows’:

efficient cause: population, community, organisation

generative cause: ideals, ideology, taste, ethics, ambition, spirit, style, world view

material cause: minerals, money, national income, profitt

formal cause: knowledge, technology, method

conditional cause: geography, climate, neighbouring societies/communities, infrastructure

institutional cause: laws and regulations, markets, government

exemplary cause: heroes, myths

I have used this causality to reconstruct several cases of societal development, as narrated by Bardi (2017): the fall of the Roman empire, the Irish famine in 1845-1850, the fall of the Maya’s, transition of power from Spain to England in the 17th century, the Tokugawa/Edo rule of Japan under relative stability from1600 to 1850 (Meiji restoration), as follows:

Fall of the Roman empire:

efficient cause: a variety of heterogenious peoples

material cause: dessication and depletion of arable land, yielding shortages of food, depletion of silver and gold mines in Spain, and one-sided trade of silks with China, causing shortage of coins for trade

conditional cause: conquest by Goths and Vandals

generative cause: weakening of military spirit, rise of peace-oriented Christianity, urge to luxury

institutional cause: overextension of the empire to the north, with communication restricted to roads, delegation of defense of frontiers to local tribes, internal strife.

Irish famine:

efficient cause: proliferation of small scale farming

material cause: monoculture of mostly potatoes

conditional cause: steep, rocky coasts that precluded ports as a basis for fishing, no coal, as in England,dessication, contageous potato disease

institutional cause: monoculture of potato farming, with little industry, deforestation

generative cause: proclivity towards large families, enhanced rather than controlled during the famine, causing overpopulation and shortage.

 

The Maya’s:

Conditional cause: dessication, conquest by the Spanish, bringing diseases the population was not resistent to

Institutional cause: internal rivalry

 

Transition of sea power from Spain to England in the 17th century:

material cause: depletion of gold and silver mines in Spain, yielding a lack of currency

conditional cause: dessication of the land, deforestation robbing Spain of wood for building ships, and for smelting iron, while England had coal and could build iron ships.

Institutional cause: depletion of resources

 

Tocugawa/Edo rule, where the application of causality focuses on stability, not collapse:

material cause: currency, arable land

Institutional cause: no monoculture but a variety of produce and crafts, centralistic, military, hierarchical governance imposing obedience, no depletion of resources. It ended ended around 1850, with the Meiji restoration that imposed access for foreigners, and democratic governance, with a parliament.

generative cause: no primacy of profit making but orientation to hierarchy and family

conditional cause: coastline amenable to fishing, international trade but closure to foreign traders (except for the Dutch, in a limited way),

 

I am sure the analysis could be extended, and I have not checked the validity of Bardi’s account, but I wanted to show the fruitfulness of this multiple causality. I am curious what historians think of it. Is it valid, fruitful?

 

Bardi, U. 2017, The Seneca effect, Springer.

MacCumber, J. 2007, Reshaping Reason, Toward a new philosophy, Bloomington IN: Indiana University Press.

Nooteboom, B. 2019, Uprooting economics, A manifesto for change, Cheltenham: Edward Elgar.

 

 

      

541. Ontologies and dynamic systems

ontology is the philosophy of what exists in the world, is about the ‘furniture of the world’. What are the properties of  things that exist? ‘Things’ here can be anything: an object, an organism, a community, a technical system, world trade. Ideally, there would be only one ontology that covers everything. However, like any theory, ontology is not some magical grasp of all truth that represents reality beyond our perception. It is a device for ordering our perceptions (MacCumber, 2007), and there may be different ontologies for different kinds of things.

 According to the dominant ontology, things have a boundary, an internal structure and external interaction with other things. There can be a hierarchy of things, with elements in a coherent system, that in turn is an element in a ‘higher ‘level’ system, such as organs in a body, or people in a community.

 Systems are subject to the law of increasing ‘entropy’, i.e. the dissipation of energy and structure. A pan of hot water, when taken from the stove, will dissipate its heat to its environment. An organism that no longer ingests energy in the form of food will decay. Life is a fight against increasing entropy, maintaining the distinction of internal structure.  

 Systems are networked, with relations between the elements, called ‘nodes’. This is a second ontology, of nodes in a network, which renders the boundaries of the elements of a system permeable, although that was also implied, to some extent, by the external interaction between things that affects internal structure. In some treatments of this ontology, however, no identifiable or stable identity of things is left: the node is entirely determined by its network positions.

 In the body those ‘ties’ between nodes are streams of blood, transporting oxygen and food, hormones, or electrical impulses along neurons. In commuties they are relations of trade, family, care, friendship, sex, fighting, organisation, hierarchy, communication, contamination, hypes, mobs, voting. The connections between ‘nodes’ can yield complementarity, sustaining each other, maintaining a trembling equilibrium in the system, with small deviations and repair , called ‘homeostasis’. But it can also propagate collapse. When one node collapses, for whatever reason, that can burden or withhold support to  a neighbouring node, and so on.

 Such positive  feedback can cause collapse of the entire system, as in the financial system in 1930 and 2008, and the lockdown of society, in an attempt to stop the propagation of infection, as in Covid-19. Such system collapse is studied in the ‘theory of dynamic systems’  (Holland, 1992; Bardi, 2017). Collapse of the world economic system was studied by the ‘Club of Rome’, with its ‘Limits to Growth’, in the 1980’s (Bardi, 2017).

 Such collapse is often faster than the growth of the system, which is called the ‘Seneca effect’, attributed to the Roman stoic philosopher Seneca (Bardi, 2017). An easy way to explain this difference in speed of growth and collapse is that growth is subject to ‘negative feedback’, due to increasing resistance to the addition of something new, in ‘decreasing returns’ to the efforts involved, as the system becomes more complex and resources and space for extension get depleted. The decline, on the other hand, has positive feedback, in the propagation of the demise of a node to neighbouring nodes, repeated in increasing numbers.

 A third ontology is that of internal forces that adapt the internal structure of things to changes in the environment, studied in the theory of ‘Complex Adaptive Systems’ (CAS; Holland, 1992). Elements that contribute most to a collective endeavour are reinforced, by the ‘attribution of merit’, and the ones with low merit decline and disappear. The collective endeavor may be the maintenance of homeostasis, or creation of a new one. This is how neuronal networks in the brain develop (Edelman, 1987). Such evolutionary adaptation can also apply to the ‘rules’, the connections between nodes. Some rules may arise for trial randomly, as in in the form of ‘genetic algorithms’ that mimick the random generation of new forms of life in the ‘crossover’ between chromosomes in the sexual reproduction of animals. They may, when succesful, grow to dominance.This dynamic ontology is redolent of previous ontologies of adaptive force, such as Nietzsche’s ‘will to power’.

 The difference between the three ontologies is not necessarily limitative to any of them. I already indicated how the node ontology can be added to the dominant ontology, with permeable boundaries to things. Adaptive force also may be added, in a CAS.

 How about current society? Is there a stable homeostasis? Is it resilient to deviations? If not, can the system be adaptive? Bardi (2017) compared the decreasing returns to scale of growth, in burgeoning complexity, piling up regulations, lifting bureaucracy to new heights, to the notion of entropy. I am not sure that is valid. Another notion, connected perhaps is that of EROI, Energy Return On Investment, i.e. the energy one gets out of a system minus the energy one has to put in. As resources get depleted and an increasingly complex system requires more and more energy to press out an addition. When EROI becomes negative, the sysem is no longer viable.

 As past homeostasis is breaking down, in a rising dominance of self-interest over civility, yielding an atomisation in polarised lumps and bumps of people that no longer communicate with each other, there seems to be an increasing threat to democracy, and perhaps autocracy is the only way to restore homeostasis, in imposing regulation, reducing freedom, to ensure homeostasis. Or can democracy  survive in some form of controlled anarchy? I have to further think this out.                

 Bardi, U. 2017, The Seneca effect, Springer.

Edelman, Gerald M. 1987, Neural Darwinism: The theory of neuronal group selection, New York: Basic Books.

Holland, J.H. 1992, ‘Complex Adaptive Systems’, Daedalus, 121/1, 17-30.

MacCumber, J. 2007, Reshaping Reason, Toward a new philosophy, Bloomington IN: Indiana University Press.

 

 

540. Mutual exclusion: The case of economics and business studies.

This item is an abridged version of a paper I published in Academia Letters, in 2021. The full version is posted on the page of essays, on the website www.bartnooteboom.nl

 Abstract

 This letter narrates the failure of an attempt to integrate economics and business studies in a joint research institute cum PhD school, analyses the fundamental underlying differences in basic assumptions and methods, and tells of the recurrence of the problem in an  appoinment procedure at the Royal Netherlands Academy of Arts and Sciences.

 Here I present a case study that happens to be my personal experience. That may seem cantankerous and vindictive, but it seems somewhat artificial to pretend that it is the experience of someone else. This letter may read as a crusade against maintream economics, as a reviewer suggested, but that is perhaps not so bad, considering the damage right-libertarianism has caused society, with increasing disparities between rich and poor.  

 Exclusion

 Lakatos (1970) proposed that scientists are committed to a ‘research programme’, of which there may be several, in a discipline, with a series of theories that share a ‘hard core’ of basic assumptions, with the ‘negative heuristic’ that they  are not to be challenged, shielded by a ‘protective belt’of subsidiary assmptions. When a theory in the programme fails, changes are made in this protective belt rather than the core. Theories that violate the core are ostracised or ignored, and are excluded from journals or edited books dedicated tot he programme. This makes science inherently conservative. Tribal culture dominates science.

Conservative as this is, there are arguments for it. One cannot look at all directions at the same time, and a certain perspective is needed for focus, coherence and analytical rigour. There is also an evolutionary argument: if there were no different species, and all animals could interbreed, in due course no separate species would remain, and rivalry and evolutionary selection would vanish. This may yield an argument against interdisciplinarity.

On the other hand, innovation arises from variety, novel combinations, to generate new forms, genotypes, to be submitted to evolutionary selection. In nature, such variation is random, by novel configurations of genes in chromosome crossover, in sexual reproduction, copying errors of DNA, and mutations of genes. In society, in science and politics, it is not entirely random, but informed by inference, experimentation, and artificial selection (in simulation or testing of concepts or prototypes, in learning systems. This yields an argument in favour of some form of interdisciplinarity.

Behavioral factors involved are the urge of scientists, and people in general, to affiliate and congregate with like-minded people who more easily extend recognition to each other than to outsiders. They seek like-minded parters to collaborate with, who are prone to recognise it and refer to it, which furthers careers. It also takes less effort of understanding ‘out of the box’.

A response to exclusion by a programme, whereby one cannot gain access to publication channels, is to craft one’s own association in a new programme, with one’s own proprietary journal, conference and publishers.

 Economics

 Programmes of unorthodox economics emerged from criticism of orthodox economics. An example is  ‘Institutional economics’ (Hodgson, 1998), which instituted its own ‘Journal of Institutional Economics’ and dedicated conferences. Another is ‘Evolutionary economics’ (Nelson and Winter, 1982),  with their own ‘Journal of Evolutionary Economics’ and the ‘Journal of Economic Issues’. A third is ‘Behavioural Economics’, though that has been incorporated to some extent in mainstream economics. Other examples are a programme in studies of trust (Bachmann and Zaheer, 2012), with the ‘Journal of Trust Research’ and studies of ‘Post-Keynesian Economics’. These examples illustrate that there are also different research programmes within a discipline.

            In Institutional economics, institutions are ‘rules of the game’ (Hodgson, 1989), with legal arrangements such as property rights, rules to protect the environment and constraints on advertising, and beyond those the effects on economic issues of cultural habits and rules,  language, power groups, lobby groups, network effects, corruption and politics. One type of institutions is so-called ‘transaction costs’, which are costs of the market, such as the costs associated with supply and demand finding each other, judgement of quality, negotiation, crafting agreements and contracts, controlling their execution, litigation in case of breach, and so-called ‘specific investments’ in contracts or collaborative arrangements that are lost, not useful in other relations, when the relation breaks. Those can be used to leverage power of threatening to walk out if not given  a greater share of jointly produced profits. These costs can yield a reason not to use markets but integrate activities in a single organisation.  

            Evolutionary economics looks at the economy as an ecosystem, governed by the evolutionary principles of variety creation, rivalry and selection in markets, and transmission of surviving success in imitation, growth, and education and training. In biology variety creation arises from chromosome crossover, in sexual reproduction, and copying errors and mutations of genes, in the economy it arises in entrepreneurship and environmental and technological change. The key feature of evolutionary theory is that there is no ‘intelligent design’, as opposed to economic planning and control. Evolutionary economics has its puzzles: What consitutes the selection environment; not only markets but also institutions. Who or what is being selected: firms or ideas and practices, and what does ‘survival of the fittest’ mean, when ideas can be partly adopted from firms that fail? Firms can merge to survive. Transmission entails communication,  and there variety arises from variety of understanding and interpretation, so that variety generation and transmission get entangled. Also, institutional effects of lobbying and political influence can yield ‘co-evolution’, i.e. influence of the units to be selected on the selection environment, more so than found in biology, and when strong, this effect can prevent effective selection.

Trust beyond a balance of reciprocal advantage, in mutual dependence, is not accepted by mainstream economists, as seen to be in conflict with competition in markets, which enforce breach of trust to maximise advantage, needed for survival. Trust researchers have objected that a leap of faith beyond calculable advantage is needed for collaboration in innovation, which also needed to survive in markets (Moellering, 2009).

Behavioural economics makes use of insights from social psychology, in the role of subconscious, routinised ‘decision heuristics’ that limit free will and rationality. While the heuristics are non-rational, they can be adaptive, assisting survival, and in evolution have developed for that reason.  

Economics and business

I experienced the cliff between economics and business when I was appointed scientific director of a research institute cum PhD school at a university  in Netherlands, by the board of the university, in the 1990’s, with the task of integrating those disciplines.  Such integration stands to reason: business forms an important part of the economy. I accepted the commission because I saw parts of economics as promising bridgeheads for making the connection: Evolutionary, Institutional, Industrial, Behavioural  and Transaction Cost Economics. Unfortunately, it turned out that those parts of economics were not represented in the Economics Faculty. At the Business Faculty there were practitioners of Systems Theory, Organisational Behaviour, Personnel Management and Legal Management who  wanted to include sociology, psychology and law, which was anathema to the economists. I tried to cross the cliff, but the effort was thwarted by both sides. The rejection was mutual. I failed miserably, at least substantively, and could only erect a facade, a stage set, behind which everybody just continued to play his or her familiar game. After much wasted effort, I left that university, but I remained intrigued by the failure: what was it that made integration so difficult? After a time I arrived at  the following analysis.

For mainstream economics the core had, still has, the following basic assumptions and perspectives:

-          It is outcome oriented, constructing models that maximise utility or efficiency (Hodson, 2019), taking that as a goal of policy, regardless of how that outcome is to be achieved. Indeed, in some areas such an approach is valid and useful, such as in optimising the scheduling of a refinery or a loading facility for ships, a stream of goods, conditions for efficient timing and queuing, and optimal location, to name a few things that are relevant to business. It mostly misfires in other areas, such as strategic management, personnel management, leadership, innovation, collaboration, and the development of financial instruments. An interesting and useful innovation in economics was game theory, analysing strategic interaction, but it was limited in its assumptions that players knew all options and their potential ‘pay-offs’.

-          It is aimed at mathematical models, as the paragon of being scientific.

-          It assumes rationality in making choices

-          It uses statistics to calculate risk, where one does not know what is going to happen, knows what can happen, but cannot deal with ‘real’ uncertainty of not knowing all that can happen.

Business, by contrast, requires he following perspectives:

-          It is process oriented, in designing and guiding processes, of production, marketing and distribution, organisation, strategy making, and learning.

-          It is not limited to mathematical models, because the required  measurement is not always possible, and it is not always clear what the available options are.

-          It cannot assume rationality because people and sytems are often not rational.

-          It has to face uncertainty, beyond risk, in innovation and strategy.

In retrospect, in view of these fundamental differences, it  is not surprising that economics and business could not be integrated. They reside in different worlds, with different perspectives, in different cultures.

            Mainstream economics had a rhetorical comparative advantage, in the eyes of practitioners and policy makers, in its use of mathematics, and the clarity and simplicity of optimal outcomes, in comparison with the complexity of evolution, seen as muddling and yielding no determinate outcomes, in the absence of intelligent design. It was imposssible to predict the outcomes of evolution. I was member of an advisory committee for a Max Planck institute for evolutionary economics in Jena, in Germany, and once we had to defend the institute in front of a visit of board members of the Max Planck, we failed to make the merit of evolutionary economics clear, and the institute was abolished and replaced by an institute for mainstream economics.

The situation has since changed, in the emergence of ‘Agent Based Simulation’, whereconduct is simulated in a computer on the level of interacting agents, to model markets and their failures, in evolutionary processes. See T. Klos & B. Nooteboom (2001).  This serves to also give a mathematical, rigorous gloss to evolutionary economics. That method has problemsof its own, in that complexity explodes as one adds variables and parameters, and it becomesdifficult to understand what is going on, and to test models. One option is to compare aggregateoutcomes with available statistics.

 Conflict in the academy

The cliff between ecoomics and business studies re-emerged many years later, in 2020, in the Royal Netherlands Academy of Arts and Sciences, of which I had become a member in 2000. This has a section for economics and business studies, and the problem arose on the occasion of the nomination a new member. Someone submitted a proposal, which I seconded, for the nomination of a scholar with a background in applied psychology, with a wealth of publications in excellent journals in the area of organisational leadership. The proposal was waylaid by the economists, on the ground that she had not published in top economic journals. I came up in arms, on the ground that economics and business had been combined in the academy not because of some common method or theory, but because of being related phenomena in the economy. I sent around a brief statement of the differences between the disciplines, along the lines indicated above, with a proposal for a debate on it. The only response I received was a thank-you for ‘offering these personal reflections’. No one responded to my suggestion for a debate. I went to he presidency of the Academy with the suggestion for a separate section for the programme of business studies, but was fobbed off with the assurance that the current leadership of the joint section would attend to the issue. That is the last I heard of it. The mutual exclusion of economics and business studies, to the point of refusing debate, but this was accepted without debate, even in the Academy.          

References             

      Bachmann, R, and A. Zaheer (eds.), Advances in trust research, Cheltenham UK: Edward Elgar, 2012.

   Hodgson, G. (1998), ‘The approach of institutional economics’, Journal of EconomicLiterature,36 March, p. 166-192  

     Hodgson, Geoffrey, (2019),  Is there a future for heterodox economics?,Cheltenham UK:Edward Elgar.

Kahneman, D. and A. Tversky 1979, ‘Prospect theory: an analysis of decision making under risk’, Econometrica, 47: 263–91.

Kahneman, D., P. Slovic and A. Tversky (eds) 1982, Judgment under Uncertainty:Heuristics and Biases, Cambridge: Cambridge University Press.

      Klos, T. and  B. Nooteboom 2001, Agent-based computational transaction cost economics, Journal of Economic Dynamics and Control, 25: 503-26.

Lakatos, I. 1970, 1978, The methodology of scientific research programmes, Cambridge: Cambridge University Press

     Moellering, Guido 2009, ‘Leaps and Lapses of Faith: Exploring the Relationship Between Trust and Deception’, in: B. Herrington (ed.) Deception: From Ancient Empires to Internet.

Nelson, R.R. and Winter, S. 1982, An evolutionary theory of economic change, Cambridge: Cambridge University Press.