MS Brown
Jul 1, 1980; 21:505-517
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JL Dixon
Feb 1, 1993; 34:167-179
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Weerapan Khovidhunkit
Jul 1, 2004; 45:1169-1196
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Dawn L. Brasaemle
Dec 1, 2007; 48:2547-2559
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AE Christian
Nov 1, 1997; 38:2264-2272
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JP Segrest
Feb 1, 1992; 33:141-166
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Creon Butler appointed to lead Global Economy and Finance Programme News Release sysadmin 22 October 2019

Creon Butler has been appointed to lead the Global Economy and Finance programme at Chatham House, joining the institute at the beginning of December. He will also form part of the institute’s senior leadership team.

Counter-terrorism measures and sanctions: How to avoid negative consequences for humanitarian action? 9 September 2021 — 2:00PM TO 3:30PM Anonymous (not verified) 21 July 2021 Online

Exploring current endeavours to address the tensions between counter-terrorism measures, sanctions and humanitarian action.

Counter-terrorism measures  address broad forms of support to terrorist acts. Their expansion, internationally and domestically, has given rise to new points of friction with international humanitarian law. Unless the measures include adequate safeguards, they  can impede humanitarian action. Country-specific sanctions imposed for other objectives, such as ending conflicts or protecting civilians, raise similar challenges for humanitarian action. 

These problems are not new, but solutions at international and national level remain elusive. 

At this panel event, which marks the launch of a new Chatham House research paper, panellists explore current endeavours to address the tensions between counter-terrorism measures, sanctions and humanitarian action.

• What are the current dynamics and developments at Security Council level?  
• What are the opportunities now that the UK is developing its independent sanctions strategy? 
• What challenges do counter-terrorism requirements in funding agreements for humanitarian action  pose? 
• What is necessary to make progress?

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Rhodopsin is a canonical class A photosensitive G protein–coupled receptor (GPCR), yet relatively few pharmaceutical agents targeting this visual receptor have been identified, in part due to the unique characteristics of its light-sensitive, covalently bound retinal ligands. Rhodopsin becomes activated when light isomerizes 11-cis-retinal into an agonist, all-trans-retinal (ATR), which enables the receptor to activate its G protein. We have previously demonstrated that, despite being covalently bound, ATR can display properties of equilibrium binding, yet how this is accomplished is unknown. Here, we describe a new approach for both identifying compounds that can activate and attenuate rhodopsin and testing the hypothesis that opsin binds retinal in equilibrium. Our method uses opsin-based fluorescent sensors, which directly report the formation of active receptor conformations by detecting the binding of G protein or arrestin fragments that have been fused onto the receptor's C terminus. We show that these biosensors can be used to monitor equilibrium binding of the agonist, ATR, as well as the noncovalent binding of β-ionone, an antagonist for G protein activation. Finally, we use these novel biosensors to observe ATR release from an activated, unlabeled receptor and its subsequent transfer to the sensor in real time. Taken together, these data support the retinal equilibrium binding hypothesis. The approach we describe should prove directly translatable to other GPCRs, providing a new tool for ligand discovery and mutant characterization.

A. I. Aptekarev and M. L. Yattselev
Trans. Moscow Math. Soc. 83 (), 251-268.
Abstract, references and article information

Mining and the Circular Economy: Implications for the Minerals and Metals Industries 6 November 2017 — 4:00PM TO 5:30PM Anonymous (not verified) 31 October 2017 Chatham House, London

Realizing the Potential of Extractives for Industrial and Economic Development 18 October 2018 — 5:30PM TO 7:00PM Anonymous (not verified) 3 October 2018 Chatham House | 10 St James's Square | London | SW1Y 4LE

Over the past two decades, the extractives industries have risen in importance for many low- and middle- income countries their prospects for economic development and poverty reduction. During a period of rising commodities prices, the development of extractives became increasingly attractive to both governments and companies. There was - and remains - much discussion about their potential to support inclusive development.

However, there are also risks and uncertainties associated with the extractives industries and many things can, and do, go wrong. Fluctuations in commodity prices can be hard to manage and can lead to considerable fiscal pressures. In the longer-term, climate change and the various policy responses to this, will profoundly affect the extractives sector as renewables replace fossil fuels in the global energy mix.

Managing the extractives sectors will therefore remain highly challenging especially in low-income countries where institutions are often weak. This roundtable will bring together some of the foremost academics and practitioners working in the extractives industries and also in economic development to discuss a major new UNU-WIDER study Extractive Industries: The Management of Resources as a Driver of Sustainable Development.

Attendance at this event is by invitation only.

The Electric Vehicle Revolution: Impacts on Oil Economies and Industry 24 January 2019 — 8:15AM TO 9:45AM Anonymous (not verified) 3 December 2018 Chatham House | 10 St James's Square | London | SW1Y 4LE

Electric vehicle (EV) deployment is gathering pace: the Norwegian government thinks that EV subsidies will be unnecessary by 2025 as they reach parity with diesel and petrol vehicles.

China has stipulated that EVs comprise 12 per cent of vehicle sales by 2020 while more governments are committing to banning diesel and petrol vehicles.

These developments are expected to be replicated as urban air pollution rises up the political agenda while technological developments and falling costs have given rise to ambitious forecasts on the increase in the deployment of EVs and the demise of the internal combustion engine.

Considering this, the presentations and initial discussion focus on:

• The influence of new technologies on the automotive landscape, including autonomous vehicles.
• How the automotive and oil companies are adjusting their business models to accommodate and encourage the rise in EVs.
• The risks and opportunities for the deployment of EVs for incumbents and new market actors.
• The role of government for example in public procurement and infrastructure development.
• The potential for modal shift and its impact on oil demand.

The discussion then seeks to explore the need for benchmarks of change including data and metrics to understand the changing risk landscape and the implications for different actors.

Finally, the discussion focuses on the speed of transformation and what this means for existing and new market actors.

What's next for environmental peacebuilding? Lessons learned and opportunities from conflict-affected states 17 February 2021 — 3:00PM TO 4:00PM Anonymous (not verified) 8 February 2021 Online

 This event explores lessons and opportunities from conflict-affected states.

In the field of peacebuilding, scholars and policymakers increasingly recognize the importance of environmental restoration, afforestation and infrastructural renewal for creating the sustainable livelihoods necessary for successful peacebuilding efforts.

Featuring academics writing for International Affairs on environmental peacebuilding in Colombia, Yemen and the Sahel, this webinar discusses the policy implications of the turn to environmental peacebuilding.

This event is part of the Chatham House’s Environment and Society Discussion Series in which the Energy Environment and Resources Programme brings together leading academics and policymakers to discuss key issues in environmental policy.

In particular, this event focuses on the role of environmental peacebuilding in creating sustainable livelihoods. From the impact the destruction of infrastructure can have on poverty as a driver of conflict, to the role environmental peacebuilding can play in bringing communities together by creating sustainable shared spaces of employment, the importance of the environmental livelihood creation is difficult to overstate.

Panellists focus on how policymakers can best encourage inclusive and sustainable livelihood creation and on addressing the key challenges such approaches face in the context of environmental peacebuilding efforts.

Climate finance and conflict dynamics on the road to COP27 21 September 2022 — 1:00PM TO 2:00PM Anonymous (not verified) 9 September 2022 Online

Stakeholders discuss the role of conflict and conflict sensitivity in climate finance and action.

With climate change, fragility and conflict challenges worsening, the role of international climate finance is more urgent than ever.

From the implementation of climate finance and who it reaches to the rush for renewable energy, the inclusion of conflict analysis and conflict sensitivity principles often remain absent from climate finance discussions and planning.

With COP27 around the corner and for the occasion of International Peace Day, stakeholders ranging from government representatives to climate activists discuss their perspectives on the role of conflict and conflict sensitivity as part of climate finance and action.

This event was organized in partnership with International Alert.

Artificial Intelligence Apps Risk Entrenching India’s Socio-economic Inequities Expert comment sysadmin 14 March 2018

Artificial intelligence applications will not be a panacea for addressing India’s grand challenges. Data bias and unequal access to technology gains will entrench existing socio-economic fissures.

Artificial intelligence (AI) is high on the Indian government’s agenda. Some days ago, Prime Minister Narendra Modi inaugurated the Wadhwani Institute for Artificial Intelligence, reportedly India’s first research institute focused on AI solutions for social good. In the same week, Niti Aayog CEO Amitabh Kant argued that AI could potentially add $957 billion to the economy and outlined ways in which AI could be a ‘game changer’.

During his budget speech, Finance Minister Arun Jaitley announced that Niti Aayog would spearhead a national programme on AI; with the near doubling of the Digital India budget, the IT ministry also announced the setting up of four committees for AI-related research. An industrial policy for AI is also in the pipeline, expected to provide incentives to businesses for creating a globally competitive Indian AI industry.

Narratives on the emerging digital economy often suffer from technological determinism — assuming that the march of technological transformation has an inner logic, independent of social choice and capable of automatically delivering positive social change. However, technological trajectories can and must be steered by social choice and aligned with societal objectives. Modi’s address hit all the right notes, as he argued that the ‘road ahead for AI depends on and will be driven by human intentions’. Emphasising the need to direct AI technologies towards solutions for the poor, he called upon students and teachers to identify ‘the grand challenges facing India’ – to ‘Make AI in India and for India’.

To do so, will undoubtedly require substantial investments in R&D, digital infrastructure and education and re-skilling. But, two other critical issues must be simultaneously addressed: data bias and access to technology gains.

While computers have been mimicking human intelligence for some decades now, a massive increase in computational power and the quantity of available data are enabling a process of ‘machine learning.’ Instead of coding software with specific instructions to accomplish a set task, machine learning involves training an algorithm on large quantities of data to enable it to self-learn; refining and improving its results through multiple iterations of the same task. The quality of data sets used to train machines is thus a critical concern in building AI applications.

Much recent research shows that applications based on machine learning reflect existing social biases and prejudice. Such bias can occur if the data set the algorithm is trained on is unrepresentative of the reality it seeks to represent. If for example, a system is trained on photos of people that are predominantly white, it will have a harder time recognizing non-white people. This is what led a recent Google application to tag black people as gorillas.

Alternatively, bias can also occur if the data set itself reflects existing discriminatory or exclusionary practices. A recent study by ProPublica found for example that software that was being used to assess the risk of recidivism in criminals in the United States was twice as likely to mistakenly flag black defendants as being at higher risk of committing future crimes.

The impact of such data bias can be seriously damaging in India, particularly at a time of growing social fragmentation. It can contribute to the entrenchment of social bias and discriminatory practices, while rendering both invisible and pervasive the processes through which discrimination occurs. Women are 34 per cent less likely to own a mobile phone than men – manifested in only 14 per cent of women in rural India owning a mobile phone, while only 30 per cent of India’s internet users are women.

Women’s participation in the labour force, currently at around 27 per cent, is also declining, and is one of the lowest in South Asia. Data sets used for machine learning are thus likely to have a marked gender bias. The same observations are likely to hold true for other marginalized groups as well.

Accorded to a 2014 report, Muslims, Dalits and tribals make up 53 per cent of all prisoners in India; National Crime Records Bureau data from 2016 shows in some states, the percentage of Muslims in the incarcerated population was almost three times the percentage of Muslims in the overall population. If AI applications for law and order are built on this data, it is not unlikely that it will be prejudiced against these groups.

(It is worth pointing out that the recently set-up national AI task force is comprised of mostly Hindu men – only two women are on the task force, and no Muslims or Christians. A recent article in the New York Times talked about AI’s ‘white guy problem’; will India suffer from a ‘Hindu male bias’?)

Yet, improving the quality, or diversity, of data sets may not be able to solve the problem. The processes of machine learning and reasoning involve a quagmire of mathematical functions, variables and permutations, the logic of which are not readily traceable or predictable. The dazzle of AI-enabled efficiency gains must not blind us to the fact that while AI systems are being integrated into key socio-economic systems, their accuracy and logic of reasoning have not been fully understood or studied.

The other big challenge stems from the distribution of AI-led technology gains. Even if estimates of AI contribution to GDP are correct, the adoption of these technologies is likely to be in niches within the organized sector. These industries are likely to be capital- rather than labour-intensive, and thus unlikely to contribute to large-scale job creation.

At the same time, AI applications can most readily replace low- to medium-skilled jobs within the organized sector. This is already being witnessed in the outsourcing sector – where basic call and chat tasks are now automated. Re-skilling will be important, but it is unlikely that those who lose their jobs will also be those who are being re-skilled – the long arch of technological change and societal adaptation is longer than that of people’s lives. The contractualization of work, already on the rise, is likely to further increase as large industries prefer to have a flexible workforce to adapt to technological change. A shift from formal employment to contractual work can imply a loss of access to formal social protection mechanisms, increasing the precariousness of work for workers.

The adoption of AI technologies is also unlikely in the short- to medium-term in the unorganized sector, which engages more than 80 per cent of India’s labor force. The cost of developing and deploying AI applications, particularly in relation to the cost of labour, will inhibit adoption. Moreover, most enterprises within the unorganized sector still have limited access to basic, older technologies – two-thirds of the workforce are employed in enterprises without electricity. Eco-system upgrades will be important but incremental. Given the high costs of developing AI-based applications, most start-ups are unlikely to be working towards creating bottom-of-the-pyramid solutions.

Access to AI-led technology gains is thus likely to be heavily differentiated – a few high-growth industries can be expected, but these will not necessarily result in the welfare of labour. Studies show that labour share of national income, especially routine labour, has been declining steadily across developing countries.

We should be clear that new technological applications themselves are not going to transform or disrupt this trend – rather, without adequate policy steering, these trends will be exacerbated.

Policy debates about AI applications in India need to take these two issues seriously. AI applications will not be a panacea for addressing ‘India’s grand challenges’. Data bias and unequal access to technology gains will entrench existing socio-economic fissures, even making them technologically binding.

In addition to developing AI applications and creating a skilled workforce, the government needs to prioritize research that examines the complex social, ethical and governance challenges associated with the spread of AI-driven technologies. Blind technological optimism might entrench rather than alleviate the grand Indian challenge of inequity and growth.

This article was originally published in the Indian Express.

Bangladesh: The Trade-Off Between Economic Prosperity and Human Rights 11 March 2020 — 1:00PM TO 2:00PM Anonymous (not verified) 28 February 2020 Chatham House | 10 St James's Square | London | SW1Y 4LE

Bangladesh’s recent gains in economic and social indices, set against its record of corruption and poor civil rights, has at times been termed the ‘Bangladesh Paradox’. Yet this label is overly simplistic; the current situation proves that these trends can coexist.

The Awami League government, in power since 2009, has increased political stability, delivered unprecedented economic and social advances, and adopted a counter-terrorism strategy to stamp out extremist groups. At the same time, it is criticized for curbing civil rights and failing to hold credible elections. However, as the two previous regimes have demonstrated, the rights situation is unlikely to improve even if the Awami League were replaced.

How did worsening rights become a feature of the state irrespective of its political dispensation? An unresolved contest between political and non-political state actors may hold the key to that puzzle. The perils of the current dispensation have recently manifested in weakening economic indicators, which jeopardize the very stability and social progress for which the country has garnered much praise.

Torin Greenwood, Jonathan Kariv and Noah Williams
Math. Comp. 93 (), 2959-2983.
Abstract, references and article information

Zhaonan Wang and Yingpu Deng
Math. Comp. 93 (), 2921-2942.
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Haiyong Wang
Math. Comp. 93 (), 2861-2884.
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Ran Gu and Bing Gao
Math. Comp. 93 (), 2837-2860.
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T. De Ryck and S. Mishra
Math. Comp. 93 (), 2643-2677.
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Constantin Carle and Marlis Hochbruck
Math. Comp. 93 (), 2611-2641.
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Sangsan Warakkagun
Conform. Geom. Dyn. 28 (), 115-130.
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Time: 10:00 AM, Location: E1.012 (Hearing Room)

Kazuhiro Ishige, Paolo Salani and Asuka Takatsu
Trans. Amer. Math. Soc. 377 (), 5705-5748.
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Jong In Han and Sijong Kwak
Trans. Amer. Math. Soc. 377 (), 5561-5581.
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