Source: Tencent Research Institute

Author: Jiang Xiaojuan (Co-Chair, International Advisory Committee of the Global Digital Economy Conference; Director, National Data Expert Advisory Committee; Former Deputy Secretary-General of the State Council; Professor, University of Chinese Academy of Social Sciences)

September 8, 2026

Conceptual Framework: The Factual, The Subjective, and The Normative

To evaluate how artificial intelligence transforms economic and social structures, humanities and social science research must distinguish among three epistemological categories:

By SOLOMOAT Editorial Team

1. The Factual: Established Realities Warrant Proportional Focus

The trajectory and structural impacts of verified technological milestones are relatively transparent. That AI significantly disrupts employment in standardized disciplines is an established reality with broad societal consensus.

Similarly, the observation that AI compounds software engineering velocity is verified. Industry telemetry from Anthropic demonstrates that frontier models like Claude Mythos have driven software engineer code output multiples to 8.0x by Q2 2026, up from historical baselines. Whether developer productivity expands two-fold or eight-fold requires little theoretical debate; empirical production data resolves the question.

Frontline technical teams observe these shifts faster than academic institutions. The scale of white-collar labor displacement across structured, repetitive, information-processing roles is already visible:

The Core Mandate: Analyzing Subjective Experience and Normative Governance

1. The Subjective: Understanding Asymmetric Social Costs

Subjective experiences cannot be aggregated into a single utilitarian index or resolved through simple majority consensus. Designing safety nets for displaced workers illustrates this dynamic: providing baseline social security transfers addresses lost income, but it fails to address lost professional development, the elimination of workplace socialization, and the erosion of personal dignity and social status.

The right to work is not merely a mechanism for financial compensation; it is an independent human right:

A similar divergence surfaces in the assertion that remote digital platform economies benefit female labor by enabling flexible home-based employment. While female storefront ownership dominates categories like apparel (83.3%), beauty (57.7%), and maternal-infant supplies (55.2%), many highly educated professionals reject this framing. Confining work to the domestic sphere can limit executive mobility, eliminate professional boundaries, and reinforce historical gender divisions. Understanding these conflicting structural experiences requires sustained qualitative social inquiry.

2. The Normative: State Policy Must Focus on the Displaced

Normative policy requires managing structural trade-offs under capital and budgetary constraints. While technologists focus on maximizing compute performance to retain international competitiveness, social scientists must analyze the distribution of social costs across economic segments.

Public policy should not focus on subsidizing market leaders who capture outsized returns from technological shifts. State intervention must prioritize the structurally displaced—those who lack the adaptive capacity to transition and whose basic rights are undermined by rapid workplace automation.

Critical institutional mechanisms require empirical analysis:

Structural Social Security Redesign: Establishing targeted transition funds, restructuring corporate transition fees on large-scale automated layoffs, and evaluating the fiscal feasibility of automation and robotics taxes.

Conditional Universal Basic Income (UBI) & Asset Distribution: While unconditional nationwide UBI remains premature under current fiscal conditions, targeted deployment models warrant research. For example, earmarking a fractional equity or dividend stake from tech initial public offerings (IPOs) into sovereign citizen funds distributes technological gains more broadly across society.

Rebalancing Capital vs. Labor Taxation: Historical tax codes allowed full value-added tax (VAT) deductions on capital equipment to incentivize hardware procurement, lowering the cost of mechanical automation relative to human payroll. Given persistent labor market displacement, fiscal policy must rebalance the tax incidence between capital investments and human labor.

Where societal consensus exists, state institutions must act decisively:

Non-Consensus Governance: Distributed Welfare Maximization

Where collective consensus on normative outcomes is absent, imposing a single centralized framework is counterproductive. Rapid technological change creates divergent economic incentives that make uniform public consensus unworkable.

Governance should adopt a distributed framework, permitting aligned stakeholder groups to form self-governing compacts based on localized agreements. Aggregating these specialized group compacts increases broader social welfare without requiring universal societal alignment.

This is evident in health data governance. While civil codes maintain strict data protections, clinical realities require flexible arrangements. Patients managing rare, terminal conditions often prioritize medical discoveries over strict data privacy, opting into specialized patient registries where full longitudinal biological and diagnostic data are shared with pharmaceutical researchers under the principle that clinical discovery outweighs data protection.

A prominent domestic model is the ALS clinical research platform Home of Mutual Aid for ALS Recovery, founded by Cai Lei. By connecting over 18,000 ALS patients willing to pool comprehensive medical records, the platform compressed clinical trial recruitment cycles from an industry baseline of 18 months down to 24 hours.

Policy Perspective

Humanities and social science research must monitor empirical technological milestones while dedicating primary research capacity to resolving subjective disparities and normative policy trade-offs.

State governance must secure a defensive floor for structurally displaced workers and enforce clear red lines against malicious use, while maintaining regulatory flexibility for distributed, specialized industry collaborations. Aligning technical advancement with diverse human demands provides a sustainable foundation for long-term economic modernization.

Frequently Asked Questions

Why should AI research focus more on displaced workers?

Productivity gains are increasingly measurable, while the unequal human costs of displacement require deeper qualitative, ethical, and policy analysis.

What policy priorities follow from this shift?

Policy should protect core rights, redesign transition support, rebalance incentives between capital and labor, and preserve room for localized governance.