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Writing, new topic on Jan 21, new task for Jan 30

Freie Universität’s AI guidelines (in German) can be found here:

13 – Tue Jan 21 1–2 PM – co-producing texts with the help of ai

Key Session Content:

  • Understand the fundamental differences between human writing processes and AI text generation
  • Avoid getting trapped in AI-dependent workflows that bypass critical thinking
  • Structure your writing process to maximize human insight while critically evaluating potential AI assistance

    Core Concepts:
    1. Human Writing Process vs. AI Generation
  • Writing as thinking vs. writing as pattern matching
  • The value of struggle and uncertainty
  • When clarity emerges through writing process
    2. Critical AI Workflows
  • Identifying when AI seems tempting (language barriers, writer’s block, time pressure)
  • Understanding what you lose by outsourcing different parts of writing
  • Developing criteria for justified vs. convenient AI use
    3. Community-Based Writing Strategies
  • Building peer support networks
  • Collaborative writing and editing practices
  • Shared resources and knowledge banks

14 – Tue Jan 28 12–2 PM – improving your text // independent writing time // peer-review

Trade paper drafts and examine them through the lens of AI co-production. Each reviewer should:

  1. Identify sections where AI assistance might be tempting but would bypass crucial thinking work
  2. Suggest alternative approaches that maintain intellectual sovereignty
  3. Find opportunities where limited AI use might be justified by clear social/academic benefit

TASK #7: Critical Writing Process Analysis
After peer reviewing each other’s drafts, submit a reflection (1-2 pages) that:

  • Takes 1-2 examples from the papers you reviewed
  • Analyzes specific passages where AI tools might be commonly used (e.g., language polishing, transitional phrases, literature summaries)
  • Discusses the tradeoffs involved (environmental cost, thinking process, accessibility needs)
  • Proposes concrete alternative strategies for addressing writing challenges through peer support and collaborative work

Submit your analysis as a PDF by e-mail from your zedat or @fu-berlin.de address to my email address, using the subject “porcupine”. Deadline Thu Jan 30 6 PM.

ai and the Middle East, Laboring Under Old Hierarchies: AI’s Fraught Inheritance in the Middle East

Kate Crawford’s incisive analysis in the “Labor” chapter of Atlas of AI reveals how technologies like artificial intelligence carry forward long-standing logics of exploitation inherent to industrial capitalism. When viewed through this lens, the Middle East emerges as a region where AI’s impact on labor is inseparable from enduring historical currents – outside forces that have continually remolded its economic and social order over centuries. AI’s ascendance in Middle Eastern workplaces today must wrestle with the weight of this contested inheritance.

The roots of the region’s prevailing labor paradigms can be traced to the encounter between the Islamic world and European powers during the colonial era. Colonial subjugation brought capita accumulation based on extractive resource industries and plantation agriculture – economic systems predicated on highly stratified labor forces. Peasants and artisans were dispossessed, while conquering powers secured compliant labor pools through mechanisms like the kafala sponsorship system still used to govern migrant workers in Gulf states.

This dynamic remade the socioeconomic fabric of Middle Eastern societies, entrenching ethno-racial hierarchies that assigned differential economic value and mobility to populations based on constructed identities like Arabic/Ajami, Berber/Arab, Turkish/Arab etc. Colonialism’s imposed hierarchies persisted after formal decolonization, shaping the incentive structures that led labor-importing nations to employ globally-sourced migrant workers in pecking orders based on national identity, gender, race and religion.

As AI systems are unleashed into this febrile environment, their propensity to mirror and amplify historical inequities comes into sharp focus. AI-based worker surveillance and management tools are proliferating in key Middle Eastern industries like construction, logistics and hospitality that disproportionately employ migrant labor from South/Southeast Asia and Africa. These data-intensive technologies enable tight control over workers’ time, movements and outputs in ways that troubled labor advocates see as further denuding agency and self-determination from vulnerable groups.

Far from the emancipatory promise of AI often touted in corporatist visions, critics argue these deployments actively resuscitate logics that date back to the coercive labor regimes of colonial plantations and workhouses. Automated technologies divorced from ethical oversight can reify the same discriminatory dehumanization – classifying workers into efficient data flows to be optimized in service of management diktats. Echoing Crawford, they position AI as the latest assemblage in capitalism’s continual refinement of labor exploitation, surveillance and control.

This damning perspective resonates when considering cases like the alleged racist facial recognition systems used by multinational construction firms during infrastructure builds for the 2022 FIFA World Cup in Qatar. Or Dubai’s vast networks of surveillance cameras and monitoring systems pervading its labor camps and Urban construction zones – a techno-extension of the disciplinary gazes once exercised from colonial overseers’ watchtowers on plantations. Likewise, AI workforce management software that atomizes physical labor into ceaseless data streams of trackable micro-tasks seems to embody the demand for ever-greater extraction of surplus value animating industrial capitalism.

Do such examples represent the vanguard of a systemic regression to new digital forms of bondage? Not necessarily – to evaluate AI’s true potential for the region’s labor futures, we must resist analytical reductionism. Artificial intelligence, like prior emerging technologies, will manifest contingent impacts across contexts based on the particularities of its design, deployment and surrounding socio-political structures. Already, we see divergent AI applications harboring emancipatory possibilities.

Take Saudi Arabia’s vision of using AI-enabled skills mapping and career-pathing platforms to boost female participation in its diversifying labor market as part of Vision 2030’s economic goals. Here, rather than entrenching biases, AI is positioned as a lever to promote inclusive growth by circumventing culturally regressive hiring norms. Similar arguments are made for AI enhancing formalization, mobility and bargaining rights for informal sector workers dominant across the MENA region who have historically existed in economic and legal precarity.

Ultimately, Crawford’s historicist framing reveals AI’s intrinsic malleability as both a vector of control and empowerment vis-a-vis labor. As an assemblage of capitalist origins, AI will tend towards being an exploitative tool in the absence of concerted ethico-political interventions. Yet conscious efforts to institutionalize equitable AI governance, data sovereignty and worker advocacy can recode its trajectory towards more liberating ends.

For the Middle East, grappling with AI’s impacts on labor means directly confronting its colonial-capitalist legacy and persisting structural inequities. Rather than uncritically imbibing fantasies of AI-driven efficiencies at any social cost, the region’s policymakers and moral voices must foster democratic, inclusive dialogues on AI’s role. Blind adoption of AI systems from monolithic Western corporations risks further entrenching labor hierarchies, enclosures and dependencies. Only by centering principles of economic justice and labor empowerment can the region’s rich history be counterweighted against AI’s tendency to resurface its darkest echoes.

In mapping AI’s expanding footprint in the present, Crawford’s work reminds us that technology’s impacts on labor are never ahistorical. The Middle East’s turbulent encounter with AI represents a pivotal node where historical ghosts and futurist ambitions intersect. How its societies navigate this juncture will be a crucial determinant of whether AI emerges as an emancipatory force or another incarnation of subjugation for the region’s masses of workers.