Week 1 HW: Principles and Practices

1. Biological Engineering Application

Proposed Tool

• I propose developing an AI-integrated risk screening platform embedded into commercial DNA synthesis pipelines.

The system would:

• Automatically analyze ordered DNA sequences
• Compare them against pathogen databases
• Detect homology to virulence factors
• Identify gene fragments that could reconstruct regulated organisms
• Flag suspicious ordering patterns across multiple transactions
• Provide risk scores rather than binary “approve/deny” outputs

The goal is to enable scalable, affordable, and rapid DNA synthesis while preventing misuse.

Why This Matters? DNA synthesis is becoming:

• Cheaper
• Faster
• Globally accessible
• Potentially decentralizable

As synthesis democratizes, so does risk.

Traditional screening (e.g., static blacklist matching) is insufficient against:

• Fragmented gene ordering
• Codon-optimized pathogens
• AI-designed novel sequences
• Distributed malicious collaboration

An adaptive AI system is necessary to manage emerging dual-use risks.

2. Governance / Policy Goals

Primary Goal:

• Ensure that scalable DNA synthesis contributes to an ethical biological future by preventing misuse while enabling constructive innovation.

Sub-Goals A. Enhance Biosecurity

• Prevent synthesis of harmful pathogen sequences
• Detect distributed or obfuscated malicious intent

B. Foster Lab Safety

• Prevent accidental ordering of hazardous constructs
• Provide contextual safety guidance during synthesis approval

C. Protect the Environment

• Prevent unauthorized creation of environmentally disruptive organisms
• Support traceability of synthetic constructs

D. Promote Equity & Constructive Innovation

• Avoid overly burdensome regulations that block small labs
• Preserve research freedom and academic creativity

3. Governance Actions

I propose three governance options involving different actors.

Governance Action 1 Mandatory AI-Based Screening for All Commercial DNA Providers

Purpose Currently:

• Many companies follow voluntary screening guidelines.
• Screening standards vary.
• Some global providers do minimal checks.

Proposed change:

• Require standardized AI-assisted risk screening for all commercial synthesis providers.

Design

• Actors:
• Federal regulators (e.g., national biosafety authorities)
• Commercial DNA synthesis companies
• International standards bodies

Requirements:

• Certified AI screening engine
• Regular auditing
• Transparent performance metrics
• Secure reporting mechanism for flagged orders

Assumptions

• Governments can effectively enforce compliance.
• AI screening reduces risk meaningfully.
• Companies will not relocate to low-regulation jurisdictions.

Risks of Failure

• Regulatory arbitrage (companies move offshore)
• AI false positives blocking legitimate research
• Over-centralization creating surveillance concerns
• Hackers targeting screening systems

Risks of “Success”

• Excessive bureaucratic friction
• Slowed innovation
• Marginalization of small biotech startups

Governance Action 2

International Licensing Framework for High-Capacity DNA Synthesizers

Purpose Currently:

• Benchtop DNA synthesizers are becoming more accessible.
• There is limited international oversight.

Proposed change:

• License advanced synthesis hardware similar to controlled chemical equipment.
• Design

Actors:

• International regulatory bodies
• Export control agencies
• Manufacturers

Requirements:

• Licensing for purchase
• Identity verification
• Usage logging
• Remote firmware updates to maintain screening compliance

Assumptions

• Hardware control reduces misuse.
• Licensing does not push synthesis underground.

Risks of Failure

• Black market synthesizers
• Open-source hardware replication
• Innovation slowdown in emerging economies

Risks of “Success”

• Increased global inequity
• Technological nationalism
• Fragmented regulatory blocs

Governance Action 3

Global Shared Biosecurity Threat Database Consortium

Purpose Currently:

• Screening databases are often proprietary.
• Intelligence sharing between companies is limited.

Proposed change:

• Create a shared international database of:
  • Regulated pathogens
  • Novel virulence signatures
  • AI-detected risk motifs
  • Suspicious ordering patterns

Design:

• Actors:
  • DNA companies
  • Academic institutions
  • National security agencies
  • International consortia

Requirements:

• Secure data-sharing framework
• Privacy safeguards
• Rapid update mechanisms
• Independent oversight board

Assumptions

• Companies will cooperate.
• Data sharing improves detection.
• Governments allow cross-border intelligence exchange.

Risks of Failure

• Data misuse
• State surveillance expansion
• Geopolitical mistrust
• Cyberattacks on centralized databases

Risks of “Success”

• Over-flagging sequences
• ias in AI detection models
• Excessive monitoring of legitimate scientists

5. Recommended Strategy

I would prioritize: A combination of:

• Option 1 (Mandatory AI Screening)
• Option 3 (Global Shared Threat Database)

I would deprioritize hardware licensing (Option 2) because:

• It is high-friction
• Likely to increase global inequity
• Difficult to enforce internationally
• Easily circumvented via distributed synthesis

Trade-offs Considered

• Privacy vs security
• Innovation vs precaution
• National sovereignty vs global coordination
• False positives vs under-detection

Audience for Recommendation

I would direct this recommendation to:

• U.S. Department of Health and Human Services
• National biosafety authorities
• International biosecurity working groups
• Industry consortia of DNA synthesis companies

The ideal approach is co-regulation:

• Government sets baseline requirements.
• Industry implements adaptive technical solutions.
• Independent oversight ensures transparency.

Week 1 Lab: Pipetting

Individual Final Project

Group Final Project