Two years into our last review on state of the artt in the area of artificial intelligence, there has been a widening gap between the seeming omnipotence of neural network models based on “deep learning”, which are offered by market leaders, and the demand for an “algorithmic transparency” emanating from the society. In this review, we will try to probe this gap, discussing what trends and solutions can help resolve the problem or lead to its further exacerbation.
1. Developments of Recent Years
First of all, what we know as strong or general AI (AGI) has become a well-established item on the global agenda. A team of Russian-speaking researchers and developers has published a book on this topic, where they provide a thorough analysis of the possible prospects of this technology. Open seminars are being held on a weekly basis during the last two years by the Russian-speaking community of the AGI developers.
Consciousness. One of the key problems concerning AGI is the issue of consciousness, as was outlined in our earlier review. Controversy surrounds both the very possibility of imbuing artificial systems with it and the extent to which it would be prudent for humanity to endow such systems with “consciousness”, if possible at all. As Konstantin Anokhin has put it at the OpenTalks.AI conference in 2018, “we must explore the issue of consciousness to prevent that AI is imbued with it.” According to the materials of a round table held at the AGIRussia seminar in 2020, one of the first requirements for the emergence of consciousness in artificial systems is the ability of AI systems to carry out “multimodal” behaviour, which implies integrating information from various sensory modalities (e.g., text, image, video, sound, etc.) by “grounding” it from different modalities in the surrounding reality, enabling them to construct coherent “images of the world”—just as humans do.
Multimodality. It is here that a number of promising technological breakthroughs took place in 2021. For example, having been trained on a multimodal dataset including text–image pairs, OpenAI’s DALL-E system can now generate images of various scenes from text descriptions. In the meantime, the Codex system, which is also developed by OpenAI, has learnt to generate software code in accordance with an algorithm written in plain English.
Super-deep learning. The race for the “depth” of neural models, while has long been dominated by the American giants Google, Microsoft (jointly with OpenAI) and Amazon, is now joined by China’s tech giants Baidu, Tencent and Alibaba. In November 2021, Alibaba created the M6 multimodal network that boasts a record number of parameters or connections (10 trillion in total)—this is a mere one tenth behind the number of synapses in the human brain, as the latest data suggest.
Foundation models. Super-deep multimodal neural network models have been termed “foundation models.” Their potential capabilities and related threats are analysed in a detailed report prepared by the world’s leading AI specialists at Stanford University. On the one hand, the further development of these models can be seen as the closest achievement on the way towards AGI, with the system’s intelligence increased by virtue of an increasing number of parameters (more than in the human brain), perceived modalities (including new modalities that are inaccessible to humans) as well as huge amounts of training data (something that no individual person could ever process). The latter allows some researchers to speculate that a “super-human AI” could be built on such systems in the not-too-distant future. However, there remain some serious issues, both those raised in the report and others discussed below.
Algorithmic transparency/opacity. The further “deepening” of deep models serves to exacerbate the conflict between this approach and the requirements of the “algorithmic transparency,” which is increasingly imperative for AI-based decision-making systems as they proliferate. Limitations on the applicability of “opaque” AI in the areas that concern the security, rights, life and health of people are adopted and discussed around the world. Interestingly, such restrictions can seriously hinder the applicability of AI in contexts where it may be useful, such as in the face of the ongoing COVID-19 pandemic, where it could help solve the problem of mass diagnostics amid a mounting wave of examinations and a catastrophic shortage of skilled medical personnel.
Totally-used AI. AI algorithms and applications are becoming ubiquitous to encompass all aspects of daily lives, be it any kind of movement or financial, consumer, cultural and social activities. Global corporations and the states that exert control over them are those that control and derive benefits from this massive use of AI. As we have argued earlier, the planet’s digitally active population is divided into unequal spheres of influence between American (Google, Facebook, Microsoft, Apple, Amazon) and Chinese (Baidu, Tencent, Alibaba) corporations. Objectively, any possible manipulations on the part of these corporations and states, since they seek to maximize the profits of majority shareholders while preserving the power of the ruling elites, will only increase as the AI power at their disposal grows. It is symptomatic that OpenAI, initially intended as an open public-oriented project, has shifted to closed source, and it is now becoming all the more dependent on Microsoft in its finances.
Energy (in)efficiency. As with cryptocurrency mining, which has long been drawing criticism due to its detrimental environmental impact, power consumption of “super-deep” learning systems and the associated carbon footprint are becoming another matter of concern. In particular, the latest results of the OpenAI Codex multimodal system, developed jointly with Microsoft, touch on the environmental impact of this technology in a separate section. Given that the existing number of parameters in the largest neural network models is several orders of magnitude less than the number of synapses in the human brain, an increase in the number of such models and their parameters will lead to an exponential increase in the negative impact of such systems on the environment. The efficiency of the human brain, as it consumes immeasurably less energy for the same number of parameters, remains unattainable for existing computing architectures.
Militarization. With no significant progress in imposing an international ban on the creation of Lethal Autonomous Weapons Systems (LAWS), such systems are being employed by special services. As the successful use of attack drones has already become a decisive factor in local military conflicts, a wider use of autonomous systems in military operations may become a reality in the near future, especially that live pilots are no longer able to compete with AI systems in the simulation of real air battles. Poor ability to explain and predict the behaviour of such systems at a time of their proliferation and possible expansion into space invites no special comment. Unfortunately, aggravated strategic competition between world leaders in both the AI and arms races leaves little hope for reaching a consensus in a competitive environment, as was stated in the Aigents review back in 2020.
2. Prospects for Development
Given the insights shared earlier on, we shall briefly discuss the possible “growth zones,” including those where further development is essentially critical.
What can the “depth” reveal? As shown by expert discussions, such as the workshop with leading computational linguists from Sberbank and Google held in September 2021, “there is no intelligence there,” to quote one of the participants. The deepest neural network models are essentially high-performance and high-cost associative memory devices, albeit operating at speeds and information volumes that exceed human capabilities in a large number of applications. However, by themselves, they are failing to adapt to new environmental conditions if not tuned to them manually, and they are unable to generate new knowledge by identifying phenomena in the environment to connect them into causal models of the world, let alone share this knowledge with other constituents of the environment, be they people or other similar systems.
Can parameters be reduced to synapses? Traditionally, the power of “deep” neural models is compared to the resources of the human brain on the basis of a whole set of neural network parameters and proceeding from the assumption that each parameter corresponds to a synapse between biological neurons, as is the case of the classical graph model of the human brain connectome, reproduced using neural networks since the invention of the perceptron over 60 years ago. However, this leaves out of account the ability of dendritic arms to independently process information, or hypergraph and metagraph axon and dendrite structures, or the possibility of different neurotransmitters acting in the same synapses, or the effects associated with interference of neurotransmitters from various axons in receptive clusters. Failing to reflect if one of these factors in full means that the complexity and capacity of existing “super-deep” neural network models is removed by dozens of orders of magnitude from the actual human brain, which in turn calls into question the fitness of their architectures for the task of reproducing human intelligence “in silico”.
From “explainability” to interpretability. Although the developments in Explainable AI technologies make it possible to “close” legal problems in cases related to the protection of civil rights, allowing companies to generate rather satisfactory “explanations” in cases stipulated by law, in general the problem cannot be considered solved. It is still an open question whether it is possible to “interpret” trained models before putting them to use, in order to avoid situations where belated “explanations” can no longer bring back human lives. In this regard, the development of hybrid neuro-symbolic architectures, “vertical” and “horizontal,” appears promising. Vertical neuro-symbolic architecture involves artificial neural networks at the “lower levels” for low-level processing of input signals (for example, audio and video) while using “symbolic” systems based on probabilistic logic (Evgenii Vityaev, Discovery, and Ben Goetzel, OpenCog) or non-axiomatic logic (Pei Wang, NARS) for high-level processing of behavioural patterns and decision-making. Horizontal neuro-symbolic architecture implies the possibility of representing the same knowledge either in a neural network, implementing an intuitive approach (what Daniel Kahneman calls System 1) or in a logical system (System 2) operating on the basis of the abovementioned probabilistic or non-axiomatic logic. With this, it is assumed that “models,” implicitly learned and implicitly applied in the former system, can be transformed into “knowledge,” explicitly deduced and analysed in the latter, and both systems can act independently on an adversarial basis, sharing their “experience” with each other in the process of continuous learning.
Can ethics be formalized? As the ethics of applying AI in various fields are increasingly discussed at the governmental and intergovernmental levels, it is becoming apparent that there are certain national peculiarities in the related legislation, first of all in the United States, the European Union, China, Russia and India. Research shows significant differences in the intuitive understanding of ethics by people belonging to different cultures. Asimov’s Three Laws of Robotics seem particularly useless as in critical situations people have to choose whether (and how) their action or inaction will cause harm to some in favour of others. If AI systems continue to be applied (as they are in transport) in fields where automated decisions lead to the death and injury of some in favour of others, it is inevitable that legislation will develop in relation to such systems, reflecting different ethical norms across countries, and AI developers working in international markets will have to adapt to local laws in the field of AI ethics, which is exactly what is now happening with personal data processing, where IT companies have to adapt to the legislation of each individual country.
3. Further Steps
From a humanitarian perspective, it seems necessary to intensify cooperation between the states leading in AI and arms races (Russia, the United States and China) within the UN framework in order to effect a complete ban on the development, deployment and use of Lethal Autonomous Weapon Systems (LAWS).
When entering international markets, developers of universal general AI systems will have to ensure that their AI decision-making systems can be pre-configured to account for the ethical norms and cultural patterns of the target markets, which could be done, for example, by embedding “core values” of the target market, building on the fundamental layer of the “knowledge graph,” when implementing systems based on “interpretable AI.”
Russia cannot hope to aspire for global leadership with its current lag in the development and deployment of “super-deep” neural network models. The country needs to close the gap on the leaders (the United States and China) by bringing its own software developments to the table, as well as its own computing equipment and data for training AI models.
However, keeping in mind the above-identified fundamental problems, limitations and opportunities, there may still be some potential for a breakthrough in the field of interpretable AI and hybrid neuro-symbolic architectures, where Russia’s mathematical school still emerges as a leader, which has been demonstrated by the Springer prize granted to a group of researchers from Novosibirsk for best cognitive architecture at the AGI 2020 International Conference on Artificial General Intelligence. In terms of practical applicability, this area is somewhat in a state similar to that of deep neural network models some 10–15 years ago; however, any delay in its practical development can lead to a strategic lag.
Finally, an additional opportunity to dive into the problems and solutions in the field of strong or general AI will be presented to participants in the AGI 2022 conference, which is expected to take place in St. Petersburg next year and which certainly deserves the attention of all those interested in this topic.
From our partner RIAC
Deployment of 5G Technology: Scrutinizing the Potential Menace & Its Repercussions globally
5G, or fifth generation, is the latest generation of mobile telecommunications technology. It promises faster internet speeds, lower latency, and greater capacity than previous generations of mobile networks. 5G technology is designed to support a wide range of new and emerging applications, including the Internet of Things (IoT), autonomous vehicles, and virtual and augmented reality. The introduction of 5G to the world is a significant development in the field of telecommunications. It is expected to have a major impact on various sectors such as healthcare, transportation, manufacturing, and entertainment. 5G networks will enable new technologies like self-driving cars, remote surgery, and virtual reality to function more smoothly and efficiently.
It is based on a number of new technologies, such as software-defined networks, network slicing, and millimetre waves, which allow for faster data transfer and a greater number of connected devices. This will allow for more efficient use of network resources and support a wider range of applications. Many countries and mobile network operators are in the process of rolling out 5G networks, and the number of 5G-enabled devices is expected to grow rapidly. However, the deployment of 5G networks is a complex and ongoing process, and there are still many technical and regulatory challenges that needs to be addressed.
Concerns & Impact:
In terms of cybersecurity, 5G networks have the potential to be more vulnerable to cyber-attacks than previous generations of mobile networks. The increased complexity of 5G networks and the use of new technologies, such as software-defined networks, could make them more difficult to secure. As the number of devices connected to 5G networks increases, so does the attack surface for cybercriminals. In terms of privacy, with the deployment of 5G networks, the amount of data that is collected and stored by mobile network operators will increase, raising concerns about the protection of personal information. 5G networks will enable new technologies, like self-driving cars, remote surgery, and virtual reality, which will generate a large amount of data. Ensuring the security and privacy of this data will be a major challenge. Also, in terms of supply chain security, the deployment of 5G networks requires a large number of components and systems from different vendors, which makes it more difficult to ensure the security of the network. There are concerns that these components, if not properly secured, could be used by malicious actors to compromise the network. The deployment of 5G networks could also lead to radiofrequency interference with existing technologies such as weather radar, satellite communication, and GPS systems, aviation navigation, and scientific research. Even, countries that are deploying 5G networks are dependent on foreign vendors for the equipment and technology needed to build and operate these networks, which creates national security concerns.
Further, there are several concerns related to the environment and health that have been raised in relation to the deployment of 5G technology. It requires the installation of many more cell towers and antennae than previous generations of mobile networks. The environmental impact of this increased infrastructure, including the potential impact on wildlife and natural habitats, is a concern. The increased use of 5G networks is likely to lead to an increase in energy consumption, which could have an impact on greenhouse gas emissions and contribute to climate change. Additionally, there have been concerns about the potential health effects of 5G technology, particularly related to the use of millimetre waves for the transmission of data. Some studies have suggested that these waves may have an impact on human health, although the majority of scientific studies have found no evidence of such effects. 5G technology uses the same frequency bands as meteorological radars and could interfere with the accuracy of weather forecasts. Such networks will increase the exposure of people to electromagnetic fields, which could have negative impacts on health, particularly for people who are sensitive to electromagnetic fields.
However, it’s pertinent to note that these concerns are being studied and addressed by governments and regulatory bodies, and steps are being taken to mitigate them. However, it’s important to be aware of these issues and take appropriate action to address them as 5G networks are deployed to ensure that the benefits of 5G technology are realized while minimizing the security, privacy, environmental and health risks.
Resolving these concerns will require a multi-faceted approach that involves cooperation between governments, industry, and other stakeholders. Governments and industry should work together to develop and implement security standards and best practices for 5G networks. This could include regular security audits and penetration testing, as well as measures to detect and respond to cyber-attacks. They should work together to develop and implement data protection and privacy policies for 5G networks. This could include measures to protect personal data, such as encryption and secure data storage, as well as clear guidelines on how data is collected, used, and shared. They should conduct further research on the potential health effects of 5G technology, and take steps to mitigate any negative impacts. This could include measures such as limiting exposure to electromagnetic fields and ensuring that cell towers are located in safe areas. They should take appropriate measures to minimize the environmental impact of 5G networks. This could include measures such as using renewable energy to power cell towers and antennae, and minimizing the impact of infrastructure on wildlife and natural habitats. They should secure the supply chain of 5G networks. This could include measures such as ensuring that vendors comply with security standards, and conducting regular security audits of suppliers.
The Indian Drone Industry is Growing Leaps & Bounds
Iranian drones have wreaked havoc in war-stricken Ukraine. When it comes to drones until a few years back it was the USA Vs China, but now all countries have realized the potential of these flying machines.
Bill Gates had predicted that drones, overall, will be more impactful than one can ever imagine or think to help society in a positive way, but sadly, today they are being used in warfare at a very large scale. Where does India stand in the Drone Making Spectre?
Today, India uses drones for a variety of causes. It has BVLOS (Beyond-visual-line-of-sight) flights, mosquito eradication drones, drones used for agricultural needs – like spraying pesticides etc., then there are seed-copters used for aforestation (planting seedballs). During the pandemic Indian drones supplied vaccines to far out regions, as estimates suggest that more than 24 lakh Indians die of treatable conditions every year simply because medicines don’t reach them on time. Drones are bridging the gap when it comes to inaccessibility of roads and other means of transport.
In India, drones can be seen everywhere, in weddings events and agricultural fields. There is a huge demand for drones and the Government is encouraging the industry to grow further. How is this emergence happening? Smit Shah, President of the Drone Federation of India is filled with ideas of zestful entrepreneurship and innovation for the Indian drone industry. He shares his views about how things in India’s Drone industry are shaping up.
“Since 2018, we have had multiple regulations and lot of work is happening on that front. Finally, in August 2021 we had our regulations liberalised. So, after multiple policy attempts and iterations we were able to crack the right policy. This is the policy of liberalisation and incentive towards the industry. Since mid 2021, we have had a boost in the ecosystem. We have multiple start-ups now, over 200 working in the drone manufacturing and technology space in the country.” says Shah.
The idea to ease the regulations has worked wonders for the industry and start-ups getting involved means a lot of innovation and experimentation is ongoing in the Indian drone industry. So, how are drones being used in governance and management? There is a lot of talk of drones being used for surveillance at borders. In what ways does the Indian Government use drones? Shah says that multiple State Governments, the Union Government, various departments and private sector corporations are now adapting to drone usage at a very large scale. The Government has launched the ‘Swamitwa Scheme’ where 6.5 lakh villages are being mapped across the entire country through drones. The National Highway Authority of India (NHAI) has mandated monthly monitoring of all highways via drones. The armed forces are looking for buying drones for security surveillance on all borders using drones. Also they are being used in tracking logistics.
India is using drones in almost all important departments, especially in defence the country is trying to procure and develop the best possible technology for which many private corporations like the Adani Group have forged Joint Ventures with major International drone component manufacturing companies.
For the purpose of warfare India is using drones on the borders to keep an eye on the enemy. It endeavours to make more advancement in the domain. How are things shaping up on that front?
“During warfare you need round the clock monitoring and intelligence and capacity building. So, surveillance capability on the borders and logistic capability on the border means transporting various kinds of resources to the border outposts, including the high altitude regions is what is being looked at now. In India, Unmanned Aircraft Vehicle (UAF), Unmanned Aerial Vehicle (UAV), Remotely Piloted Aircraft (RPA), Remotely Piloted Aircraft System (RPAS) are technological terms but are interchangeably used. All these are being used in our border security,” informs Shah.
India is rapidly scaling up its drone industry and is investing a lot on research and development. Not just for domestic use, it plans to use drones intensively for border security by the armed forces. Does India manufacture raw materials and components used in drones? What plans does it have to reduce dependence on other countries and boost its own home-built production capability? What is the road ahead?
“A majority of the components are imported from different countries. Now we have Indian start-ups and corporations who are engaged in building local supply chains and local design on drone components. The PLI incentive is encouraging for manufacturing drones and their related components in India. If we see the overall drone ecosystem of drones in India, it envisioned success lies on 4 key pillars. First is ease of doing business, under which policy was liberalised and much of the licence fees was reduced. Second is the financial incentive, like the Production Linked Incentive(PLI) under which domestic manufacturing has a 20% incentive with almost zero upfront commitment. One is not needed to do any plant or machinery investment or any minimum employment. It is a straight investment based on one’s capacity, so if you produce goods worth INR 100, you get 20% of your value addition. This is a sunrise sector, so rather than complicating incentives by tying them up with employment or revenue or upfront capital investment – it’s all straight in the face. The third part is protectionism or favouring the local industry via an import ban. At present, import of drones as a whole are banned but the import of components is not. Fourth is enhancing our own skilling, R&D, trying to becoming Athmnirbhar (Self Dependant) in every possible way and benefit our own industries. Though, a lot of technology for the smaller drones comes from across the world including China, US and Europe, for the bigger drones, like the ones used to patrol the borders or for offensive ops, it is specialized so that is coming from our partners or the domestic manufacturers,” elaborates Shah.
Many reforms by the Government have been introduced to encourage domestic production. It is confident that its own ecosystem will battle all odds and will be able to emerge as a frontrunner in drone making. The Government and industry are working in tandem to achieve this goal. In January, 2022, the Indian Government has offered a 100% subsidy or 10 lakhs, whichever is less, up to March 2023 to promote the use of drones for agricultural purposes and reduce the labour burden on the farmers. Also a contingency fund of INR 6000 per acre has been set up for hiring Drones from the Custom Hiring Centres (CHC). Together, the subsidy and contingency funds shall help farmers access latest drone technology at a very reasonable price.
Does India export drones to any other countries. If NO, by when does it intend to do so? What are its plans to become a recognized name in the drone export segment?
“Slowly and steadily India is looking at exporting. We are looking at certain initiatives to scale up our export segment and expect good results very soon. Our first goal has to be design independence. In terms of supply chains it is difficult to become 100% India made as many raw materials are imported. For that we need to have our own designs and supply chain reliability. In supply chain reliability there are 3 things, first we have domestic supply chains, second we have primary supply chains and third is we have secondary alternate supply chains. If we build good supply chains then we do not have be dependant by the traditional definition because then we have backup & balance of the supply chain. In today’s global civilization we can’t become completely independent. The right approach is to be dependant but also balanced. Some aspects of our drones may be better than others and vice versa. We are not yet ripened in this as our Information Technology (IT) sector is. India is trying to have its own electronic manufacturing fabs, so things are gaining momentum. In five years the game will totally change,” asserts Shah confidently.
The industry and Drone Federation of India is optimistic that in a few years to come India will be a champion drone manufacturer and may export to other countries as well. Be it the procurement of raw materials or other critical components it seems to be progressing fast for self-reliance in the drone industry.
Is tech industry still a boys’ club?
Authors: Ash Narain Roy and Jisha Jacob*
The Nobel Prize, says the 2022 literature laureate Annie Ernaux, is an institution “for men.” She further says that “speech has almost always been monopolised by men.” If even the hallowed Nobel Prize is still “bound to traditions” and “is perhaps more masculine,” as the French writer contends, what about the world of science and big tech?
The tech industry remains a male bastion. Citing the abysmally low percentage of female employees, the New York Times says, that the doors to the technology field “remain virtually closed to women.” The Los Angeles Times has similar observations about sexism in Silicon Valley. It says, the tech industry “lags decades behind other industries in its treatment of women.”
The big tech is far worse. Elon Musk, the new Twitter boss, often mocks advocates of the LGBT+ community. It is anybody’s guess where women will find themselves in his scheme of things. He would perhaps expect women to “follow the white rabbit.” (It is assumed if you follow the white rabbit, it will ultimately lead you to the truth). Or you may enter an alternate world. Musk isn’t playing “four-dimensional chess,” he is defending “the future of civilisation”!
Emily Chang in her book, Brotopia: Breaking Up the Boys’ Club of Silicon Valley, says that the big tech industry “has self-selected for men: first, anti-social nerds, then, self-confident and risk-taking bros.” No wonder therefore, “deep-rooted sexism prevails” in their universe and their meetings in hot tubs and at strip clubs are considered small ‘pecados’.
That women are under-represented and hold far fewer organisational positions in big tech companies like Meta, Google, Apple, Amazon and Microsoft is an open secret. As Francine Bermen and Jeniffer Lundquist say, a large number of high-profile whistleblowers are women. “Frances Haugen exposed personal data exploitation at Meta, Timnit Gebru and Rebecca Rivers challenged Google on ethics and AI issues, and Janneke Parrish raised concerns about a discriminatory work culture at Apple, among others.” (Bermen, Francine and Jeniffer Lundquist, 2022)
“Why can’t a woman be like a man” has been a grumbling refrain in most walks of life. Literature, science, films, politics have all perpetuated such perceptions. In the footnote of his famous lecture, “The two cultures and the scientific revolution,” eminent British scientist C.P. Snow said that since childhood women are given training to be a “good wife” and a “good mother.” He further said that women lack training to become a good scientist or a physicist. But he ended up saying “whatever we say, we don’t regard women as suitable for scientific careers” for which he would have been heavily trolled today. (Snow 1959) Technology is widely considered a male- dominated industry. Psychologist Janet Morahan-Martin of Bryant University explains that men are more comfortable using a computer since childhood than women. This exposure to technology in the early stage of their lives has led to the masculinization of computer culture.
Big tech and masculinity
What is masculinity? Does it really have to do anything with technology? In a larger sense, masculinity refers to how men perceive themselves. It is a manner of thinking and being that is socially formed. Victor J. Seidler of University of London offers an interesting explanation positing that men have assumed rationality as masculine based on a “rationality appropriated from and denied to others.” Men have made it a basis of male power “affecting what men see, hear and regard as important.” Brian Easlea, in his book Fathering the Unthinkable: Masculinity, Scientists, and the Nuclear Arms Race, argues that men’s propensity for science was mostly a “compensatory mechanism” for their inability to procreate and their vulnerability on the sexual level. (Easlea 1983)
Power and masculinity go hand in hand. The idea of masculinity is often associated with gaining increasingly greater power. Men now stand at the top of the technological pyramid thanks to this power. It appears that using power is fundamentally unbalanced. Men unquestionably make the important decisions. Whenever scientists are mentioned, “men” is always used as the pronoun. For instance, C.P. Snow referred to members of scientific communities as “men of science.” Men are thus at the top of the tech pyramid.
Lucie Greene, author of Silicon States: The Power of Politics of Big Tech and What It Means for our Future, cites the examples of Siri, Alexa, and all the verbal subservient assistants which normalize sexism. Twitter has an atrocious record of failing to address misogyny. Amnesty International has found women’s experience on Twitter as “toxic.” Women continue to be the victims of “digital violence.”
According to one source, women roughly represent about 25 % of technology workforce. When it comes to senior corporate leadership positions, the less said, the better. Only 8.8% of Fortune 500 CEOs are women and less than 1% of Fortune 500 CEOs are women.
The Google UK: Gender Pay Report 2018 says that there are more males than women working at Google in top leadership positions and technical occupations, Due to the underrepresentation of women in senior leadership, technical and engineering roles, and roles with a lengthy tenure, the percentage gaps persist in the majority of the leading tech businesses. Men are more likely than women to fill senior positions. Only four women appear on a random Google search of the top 48 or so tech companies.
Stereotypically gendered technology
The masculinization has produced what is known as stereotypically gendered technology. It is crucial that women work in an industry that is predominately male. Who designs a product and who stands to gain from it should be taken into consideration when it is designed. Men may design a product that is primarily used by women, which could result in subpar design. It might not fit the specifications set forth for technology that women can use. An average-height woman, for instance, cannot reach the bottom of a washing machine tub to pull the items out. Another dated example is the fact that since the 1970s, the crash test dummies used to test car safety have been modelled on men for an average male weight and height. It has only now been rectified. This digital world needs more female designers because it is mostly created by men for men.
Ironically, the early programmers were not men, but women. The 1940s saw computer operation and programming as women’s space. By the 1960s when computing gained prominence, men displaced women who were experts and as Marie Hicks states in her book, Programmed Inequality, the space was altered from a “feminized field of endeavour” to a “distinctly masculine image”. (Hicks 2018)
As per the data provided by Planet Money: NPR, women’s presence in various fields clearly shows that, while medicine, law, and physical sciences saw a significant rise in the number of female students enrolling after 1984, science and technology have seen a sharp decline in the number of female students. There was a perceptible increase between 1975 and 1984, but the trend did not last long as women were ejected from cyberspace.
Women had to learn how to utilise the room-sized supercomputers that the US employed to decipher codes during World War II. A person who programmed the first general-purpose electronic computer during the Second World War was known as a “computer.” Women were portrayed as confident, attractive, and ready to do their part to win the war. They were encouraged to join the workforce by glorifying and glamorizing the role of the working women.
Women made up a significant portion of the tech workforce throughout the World War Two and up until the 1960s. They made important contributions to science and technology.
STEM education’s impact
Women make up approximately 43% of all STEM (Science, technology, engineering, mathematics) graduates in India, one of the highest percentages in the world, but just 14% of scientists, engineers, and technicians in universities and research-development organisations. (Economic Times 2022) The underrepresentation of women in STEM fields is a problem around the world but India’s case is a curious one, despite an increase in the number of female STEM students each year, these higher education levels have not led to greater employment opportunities.
Lack of job opportunities has prompted them to turn to other avenues. Clinical psychologist Joy Harris describes such a phenomenon as “learned technological helplessness”. (Harris 2008)
Studies have shown that young girls would decide if they were good at math or science by the age of 8 – 10 years of age. It is critical to provide them the right opportunities at that young age.
The data further shows that disparity becomes acute at the undergraduate level. They prefer psychology, biological and social sciences over engineering (22%), computer science (20%), and physics (21%). Similarly in the STEM workforce, women show not much interest as compared to men. They have a very low share in the computer and mathematical sciences (26%), and engineering (16%).
Post- COVID era
Even in normal times, women bear what sociologist Arlie Hochschild calls “the double burden.” While they work for a living, they do significant amount of unpaid household work. According to a survey made in 2022, as many as 58% of Indian women lost their employment mostly due to the Covid-19 pandemic. Women were driven away from the corporate sector thanks to the rise in home duties. (Sethi 2022) This was also the time where people showed a greater dependence on technology than ever. Most jobs demanded workers to be tech-savvy. The gender gap in the economy also worsened because of the pandemic.
Rising domestic violence further accentuated the disparity. According to one source, 1 in 3 women worldwide experienced physical or sexual abuse at the hands of an intimate relationship. As a result, women were experiencing assault and looking for employment options. (UN Women: Gender equality matters in COVID -19 response)
During the worst phase of Covid and after, some people began to use social media to share their daily emotions, which allowed them to connect with others who share their perspectives. According to Statista portal, as of January 2022, Snapchat had more female users, while platforms like Facebook, LinkedIn and Twitter had more male users than female. According to another source, men use LinkedIn more often as compared to women which are 54% and 44% respectively.
The active presence of women on the social media platforms have made them vulnerable to abuses and threats of various kinds.
Online gender-based violence (OGBV) is perpetrated by using technology or a digital interface -specifically the internet or smart devices. Cyber stalking, zoom bombing, identity theft, online threats, blackmailing and cyber flashing are familiar forms of online gender-based violence. According to the toolkit, 85% of women globally face online gender – based violence. 88% of women in Asia and the Pacific have experienced OGBV. (Toolkit: 30 for 2030 UN Women 2022)
A survey on online violence against women by the Amnesty International suggests that 70% of the women who experienced some forms of online harassment have altered how they use social media, and a third of them claim they no longer express their thoughts on certain topics.
Nordic countries score higher than others on gender equality parameters. While Sweden gets top score in perceptions of gender equality, Norway tops all other nations in terms of income equality. This has been possible as the Nordic nations have established a higher degree of political consensus around issues like social equality and social solidarity. They pay women in technology more than others. As the 2018 OECD report, “Is the last mile the longest? Economic gains from gender equality in Nordic countries” notes, it is this region’s past improvements in gender equality in employment that have “contributed to economic growth.” The Nordic nations’ global reputation notwithstanding, they continue to have gender gaps in technology. Anneli Häyren, a researcher at the Centre for Gender Research at Uppsala University, Sweden, points out that there exists an idea of being gender equal, but “we have a long way to go before we are gender equal.”
The Nordic Gender Effect at Work, a report from the Nordic Council of Ministers, an advisory group, further notes that there has been “a disturbing pattern” in businesses: “the higher up the hierarchy you look, the more men you notice.” This report raises serious concerns about the gender gap. It is thus apparent that even in societies where gender equality is the norm, women and other different gender groupings may not necessarily be equally represented in all sectors, specially technology.
Some academics contend that women are less likely to pursue degrees in STEM even in countries where there is already a culture of gender equality. This behavioural pattern involves teaching topics to girls when they are still very young. It has come to surprise many like University of Essex professor Gijsbert Stoet who says, “It is a paradox…. nobody would have expected this to be the reality of our time”.
Maddy Savage’s write-up for the BBCwebsite, “the paradox of working for the world’s most equal countries,” appears puzzling. Even in Denmark, the most inclusive country in the world, “mainly white males sit at the top of many of the best-known corporations.” One explanation is that women prefer to work in public sector which limits the pool available for top private sector roles.
Engineers and IT specialists are already in short supply in the Nordic labour market. According to a study, it will soon be necessary to solve the problem because new technology will be created practically entirely by men. In the Nordic labour market, women have established themselves in the service industry. According to a survey, women have benefited most from the region’s service industry, which accounts for 80% of all employment.
Women in the tech sector continue to face toxic and gendered environment. The so-called male technical prowess as an organising principle marks the work culture. As the UN’s Economic and Social Commission for Asia and the Pacific points out, the existing under-representation of women in the technology industry is reinforcing social inequalities. “It is meaningless to talk about technological advancements if half of the population is being left behind.”
It is ironic that such gender inequalities should exist while the world embarks on the Fourth Industrial Revolution. Another worrying trend is that the Covid -19 pandemic impacted men and women differently “exacerbating current asymmetries and risking a reversal of progress made towards closing the gender gap.” Gender stereotypes have led to a gendered division of labour in the tech industry.
In 2021, the percentage of women in CEO positions globally was a mere 5.5 % and in STEM fields, it was only around 3 %. A way forward would be women’s larger presence in the STEM careers. That will not only lower the untenable existing disparities, it will embolden other women to follow suit.
Nalini Malani, a contemporary Indian artist whose creative works reflect pressing feminist issues, says that though science and technology have given us so much allowing us to talk to each other over oceans, “the human psyche hasn’t kept abreast.” However, Malani is confident that “the future is female’ and the world needs the instinctual knowledge of the female side of our brains, “otherwise we are doomed.”
Meta, the parent company of Facebook and Instagram, has announced that from February 2023 teenagers will only receive ads based on their age and location. It has also announced that it will be “removing gender as a targeting option.” It is perhaps too late, too little but it is a welcome move. If the big tech companies don’t mend their ways, they will be blamed for what Churchill chastised the Balkans: “they produce more history than they can consume.” They will be judged by the new generation for showing their own shame.
*Jisha Jacob has done Masters in Political Science from University of Delhi
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