Empowering Policymakers: Futures Literacy for Tech-Informed Foreign and International Digital Policy

Abstract

The panel explored futures literacy—the capacity to imagine, anticipate, and shape alternative futures—as a compulsory competence for diplomats and policy‑makers confronting rapid digital transformation. Drawing on complementary Indian and German perspectives, the discussion presented four contrasting 2035 scenarios for digital governance, examined how data‑ and AI‑literacy can move organisations from reactive to proactive policy‑making, and debated practical pathways for embedding futures‑oriented thinking into governmental practice, data stewardship and inclusive governance. Audience questions probed the balance between top‑down and bottom‑up approaches, the role of open‑source AI, and how diplomats can operationalise futures literacy beyond risk‑aversion.

Detailed Summary

Lars Radscheidt opened the session by positioning the Indo‑German Digital Dialogue as a long‑standing platform that brings together ministries from India and Germany to co‑design digital policy. He highlighted the need to shift from a reactive posture—where policymakers merely respond to crises—to a proactive stance that anticipates technological disruptions before they crystallise.

“We want to move from fixing problems after they appear to designing the future we want, using futures literacy as the tool.”

He outlined the session’s agenda: a brief introduction to futures literacy, presentation of four illustrative scenarios for 2035 digital governance, and a panel discussion on how these scenarios can inform policy space and decision‑making today.

2. Futures Literacy: Definition & Rationale

Sebastian Blum (Data Innovation Lab) reinforced the urgency of futures literacy:

• The past few years have seen crises dominate policy cycles, leaving little space for long‑term vision.
• Futures literacy equips decision‑makers with a plural view of possible futures rather than a single, deterministic projection.
• It leverages foresight methods—systematic techniques for exploring trends, uncertainties, and emerging signals—to reduce uncertainty, enhance resilience, and avoid lock‑in to undesirable pathways.

Blum clarified that futures literacy does not claim to predict the exact future; instead, it prepares organisations for alternative futures, enabling flexible, adaptive policies.

3. Scenario‑Based Exploration of 2035 Digital Governance

Lars Radscheidt presented four pre‑crafted, “exaggerated yet plausible” scenarios. Each scenario serves as a boundary object for discussion, illustrating distinct policy spaces that could emerge by 2035.

3.1 Scenario 1 – “Compute‑in‑a‑Box”

• Key Features
  • AI‑driven services are embedded in everyday life (health, finance, education).
  • State‑backed digital IDs are mandatory for accessing public services.
  • Large technology firms dominate the market; SMEs face high entry barriers.
  • Digital inclusion is uneven—while device penetration rises, marginalized groups remain excluded.
• Policy Implications
  • Need for inclusive digital identity frameworks that respect opt‑out preferences.
  • Regulation to curb market concentration and protect SMEs.
  • Governance mechanisms for civil‑society monitoring of AI‑driven public services.

3.2 Scenario 2 – “Erosion of the Status Quo”

• Key Features
  • Ubiquitous digital layers coexist with a resurgence of analog processes (paper receipts, physical keys) due to loss of trust in AI.
  • Cyber‑attacks, deep‑fakes, and disinformation erode confidence in digital systems.
  • Geopolitical tensions restrict cross‑border data flows, limiting AI capabilities.
  • Environmental degradation accelerates (e.g., satellite collisions).
• Policy Implications
  • Strengthen cyber‑resilience and digital forensics capacities.
  • Develop multi‑modal governance that accepts both digital and analog pathways.
  • International cooperation on data‑sharing standards despite geopolitical friction.

3.3 Scenario 3 – “Security‑First, State‑Regulated Order”

• Key Features
  • Governments impose strict, globally coordinated licensing for AI models and data centers.
  • Only a handful of government‑aligned firms control compute, data, and talent.
  • Narrow‑purpose AI improves productivity but raises unemployment and public backlash.
  • Grey markets for unsafe AI proliferate; cyber‑crime rises.
• Policy Implications
  • Balance security with innovation through transparent licensing regimes.
  • Social safety nets and re‑skilling programmes to mitigate AI‑induced job displacement.
  • International treaties that embed accountability and traceability standards.

3.4 Scenario 4 – “Commons‑Led, Co‑Creative Future”

• Key Features
  • Digital commons (open‑source AI, community‑owned networks) empower SMEs, individuals, and public institutions.
  • Strong competition authorities keep markets open; monopolies give way to decentralized cooperatives.
  • Civil society, academia, and industry co‑design governance rules anchored in human‑rights principles.
  • Open digital infrastructure reduces entry barriers, fostering sustainable, inclusive growth.
• Policy Implications
  • Institutionalise co‑design processes that involve civil society from the outset.
  • Promote open‑source funding mechanisms and public‑private partnerships for digital infrastructure.
  • Embed human‑centred oversight in AI deployment to sustain trust.

Summative Insight:
While the scenarios are deliberately extreme, they illuminate policy spaces—areas where government action could tip the trajectory toward a more desirable future. The real 2035 will likely be a mixture of these narratives, making the foresight exercise essential for strategic planning.

4. Panel Discussion: Bridging Indian & German Perspectives

4.1 Digital Literacy & AI Literacy – The German View (Rafael Leuner)

• Core Argument:
  • Digital, data, and AI literacy are not separate “IT‑training” tasks; they are intertwined with political and ethical understanding.
• Challenges Identified:
  • Over‑reliance on step‑by‑step manuals—ineffective for AI where outcomes are probabilistic and may fail.
  • Risk of using tools without grasping broader societal repercussions (e.g., bias, surveillance).
• Approach Recommended:
  • Encourage curiosity and sandbox experimentation: safe environments where civil servants can test AI, observe failures, and learn.
  • Pair technical training with scenario‑based discussions that surface ethical, legal, and diplomatic implications.

4.2 Indian Perspective – Data Stewardship & Participatory Governance (Astha Kapoor & Dr Urvashi Aneja)

• Astha Kapoor (Aapti Institute):

  • Stressed that data collected at the frontline (health workers, teachers, local administrators) is a public good that must be stewarded responsibly.
  • Highlighted gaps in existing government dashboards: poor data quality, limited accessibility, and lack of feedback loops to data providers.
  • Called for incentive structures that reward frontline workers for accurate, timely data collection, tying data quality to tangible service improvements.

• Dr Urvashi Aneja (Digital Futures Lab):

  • Emphasised that technology is never neutral; policy must embed social equity and human agency from the start.
  • Noted that many national AI strategies focus narrowly on GDP growth and compute capacity, neglecting social friction (e.g., job displacement, digital exclusion).
  • Illustrated how foresight methods surface early‑signal indicators—such as the climate impact of AI compute—that traditional economic models miss.

4.3 Synthesis & Cross‑Learning

• Hans‑Christian Mangelsdorf (German Federal Foreign Office) reinforced the diplomatic dimension: futures literacy equips diplomats with a common language to negotiate transnational data governance, AI standards, and digital rights.

• The panel agreed on several actionable recommendations:

  1. Institutionalise Futures Workshops within ministries and foreign services, using scenario‑based exercises similar to the four presented.
  2. Create Cross‑Sector Learning Labs where civil servants, data scientists, and civil‑society representatives co‑design pilots.
  3. Adopt Open‑Source AI Platforms as strategic assets to reduce dependence on a handful of global vendors.
  4. Embed Data Stewardship Metrics (quality, provenance, inclusivity) into performance dashboards for public agencies.

5. Audience Q & A

5.1 Top‑Down vs. Bottom‑Up Futures Literacy

• Question (Sree Rang, International Relations student):
  “Is futures literacy for policymakers a top‑down mandate or a bottom‑up, grassroots‑driven process?”

• Key Responses:

  • Lars Radscheidt argued that both are needed: top‑down policy frameworks set the boundary conditions, while bottom‑up insights from frontline workers and civil society provide the ground truth that shapes realistic scenarios.
  • Astha Kapoor highlighted the importance of incentivising frontline data collectors, turning them into active contributors to futures‑literacy ecosystems.

5.2 Open‑Source AI as a Policy Lever

• Question (Anonymous audience member):
  “How can policymakers encourage the development of open‑source AI to counter the concentration of power in a few megacorporations?”

• Key Responses:

  • Sebastian Blum suggested public‑funded challenge grants for open‑source AI projects that address societal priorities (e.g., climate modelling, public‑health analytics).
  • Rafael Leuner emphasized regulatory sandboxes that give open‑source innovators safe testing grounds, coupled with data‑sharing mandates that require large firms to expose anonymised datasets for public‑good research.

5.3 Diplomatic Implications of Futures Literacy

• Question (Lena Deweydy, International Serial Portal Management):
  “What does futures literacy concretely mean for diplomats—risk anticipation, technology understanding, or something deeper?”

• Key Responses:

  • Hans‑Christian Mangelsdorf noted that futures literacy extends diplomatic skill‑sets: it provides structured ways to map strategic risks (e.g., AI‑enabled disinformation), identify policy windows, and craft narrative coalitions for multilateral agreements.
  • Dr Urvashi Aneja added that it also cultivates cultural humility: diplomats learn to recognise that technological trajectories differ across societies, avoiding the “one‑size‑fits‑all” policy trap.

5.4 Emerging AI Governance Challenges

• Question (Akshay, Indo‑German Digital Dialogue participant):
  “Why, after many years of dialogue, do we still see fragmented data governance and limited progress?”

• Key Responses:

  • Lars Radscheidt admitted that institutional inertia and resource constraints slow translation of dialogue into concrete policy. He called for joint implementation roadmaps with clear milestones and shared funding pools.
  • Sebastian Blum urged the creation of joint monitoring bodies that can publicly assess progress on agreed‑upon governance metrics.

6. Announcements & Closing Remarks

• Upcoming Initiative: The Indo‑German Digital Dialogue will launch a “Futures Literacy Lab” in Q3 2025, offering quarterly scenario‑building workshops for mid‑level diplomats and policy‑makers from both countries.

• Call to Action: Panelists urged attendees to embed futures‑literacy exercises into their own organisational training calendars and to share best‑practice case studies via the conference’s digital repository.

• Closing Quote (Astha Kapoor):

  “The decisions we make today are the levers that shape the world of 2035. Futures literacy is the compass that ensures we pull those levers toward inclusive, sustainable outcomes.”

Key Takeaways

1. Futures literacy is a mandatory, not optional, skill for modern policy‑makers – it enables proactive, scenario‑based planning rather than reactive crisis‑management.
2. Four contrasting 2035 scenarios (Compute‑in‑a‑Box, Erosion of the Status Quo, Security‑First State‑Regulated Order, Commons‑Led Co‑Creative Future) map distinct policy spaces for digital governance.
3. Digital, data, and AI literacy must be taught together; technical know‑how without ethical, societal, and diplomatic context leads to risky deployment.
4. Bottom‑up data stewardship—recognising frontline workers as data generators and incentivising high‑quality data collection—is essential for trustworthy digital policy.
5. Open‑source AI and community‑owned digital infrastructure are strategic levers to counter market concentration and foster inclusive innovation.
6. Diplomats need futures literacy to negotiate multilateral AI standards, anticipate cross‑border risks, and incorporate cultural nuance into technology policy.
7. Scenario‑based workshops should become institutionalised within ministries and foreign services to embed foresight into routine decision‑making.
8. Cross‑sector learning labs (civil servants, technologists, civil society) are critical for co‑designing governance frameworks that balance security, innovation, and human rights.
9. Policy recommendations include: sandbox environments for AI experimentation, public‑funded open‑source challenges, joint implementation roadmaps for Indo‑German initiatives, and transparent monitoring bodies for digital governance progress.
10. Immediate next step – the Indo‑German Digital Dialogue’s “Futures Literacy Lab” will begin quarterly sessions in late 2025, inviting participants to co‑create actionable roadmaps for the next decade.

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See Also:

• ai-for-democracy-reimagining-governance-in-the-age-of-intelligence
• policies-for-social-and-economic-resilience-in-the-ai-age-global-south-perspectives
• the-sustainable-digital-infrastructure-accord-driving-sustainability-of-ai-infrastructure-in-the-asia-pacific-region