Week 1 HW: Principles and Practices

Homework — DUE BY START OF FEB 10 LECTURE

1. First, describe a biological engineering application or tool you want to develop and why. This could be inspired by an idea for your HTGAA class project and/or something for which you are already doing in your research, or something you are just curious about.

The biological engineering application I want to develop is rooted in agriculture, sustainability, and people. I live in Salinas, California, a region deeply shaped by farming, and I come from a background of farm working parents. Growing up, I saw firsthand the long hours spent in the fields, the physical toll of the work, and how essential yet invisible this labor often is. That experience strongly informs the kind of engineering work I want to pursue. Rather than focusing only on supporting large scale farm owners or top level agricultural operations, I am interested in developing a biological engineering tool that supports the broader agricultural community, particularly the workers and families whose livelihoods depend on the land. My goal is to design an application that promotes sustainability while also creating accessible jobs and long term economic stability. One direction I am interested in is developing biologically informed land based systems, such as soil health monitoring, waste-reduction strategies, or plant-based sensing tools, that help reduce resource waste (water, fertilizer, labor) while improving land productivity. These systems could be designed to be maintained, operated, and expanded by local communities, creating technical and environmental jobs tied directly to the land. At its core, this idea is about using biological engineering not just to optimize agriculture, but to support livelihoods, preserve land, and build sustainable job pathways for future generations. I want the outcome of this work to be more than a device or tool, I want it to be a foundation for economic resilience, environmental stewardship, and dignity in agricultural work.

2. Next, describe one or more governance/policy goals related to ensuring that this application or tool contributes to an “ethical” future, like ensuring non-malfeasance (preventing harm). Break big goals down into two or more specific sub-goals. Below is one example framework (developed in the context of synthetic genomics) you can choose to use or adapt, or you can develop your own. The example was developed to consider policy goals of ensuring safety and security, alongside other goals, like promoting constructive uses, but you could propose other goals for example, those relating to equity or autonomy.

Governance and Policy Goals for an Ethical Biological Engineering Application: To ensure that this biological engineering application contributes to an ethical future, governance and policy goals must extend beyond technical performance and address safety, equity, environmental responsibility, and human autonomy. Because this application integrates biological systems, automated machinery, data collection, and potential material transformation, it is important to establish safeguards that prevent harm while promoting constructive and socially beneficial use.

Goal 1: Non-Malfeasance (Preventing Harm): The primary governance goal is to ensure that the system does not cause harm to people, ecosystems, or surrounding communities.

Sub-goal 1.1: Environmental Protection and Containment The system must be designed to prevent unintended environmental release of biological materials, chemical byproducts, or waste outputs. This includes closed-loop processing, controlled disposal of byproducts, and safeguards against soil, water, or air contamination, especially in agricultural regions. Sub-goal 1.2: Operational and Worker Safety Automated machinery and biological processes must include built-in safety constraints, manual overrides, and clear emergency shut-off mechanisms. Instructions and system design should assume use by non-expert operators and prioritize the health and safety of farmworkers and technicians.

Goal 2: Safety, Security, and Responsible Use: As the system collects data and makes automated decisions, governance must ensure predictable behavior and prevent misuse.

Sub-goal 2.1: System Transparency and Accountability The system should log decisions (such as irrigation actions or waste processing steps) and allow users to understand why actions occur. This promotes trust, enables troubleshooting, and prevents opaque or uncontrolled automation. Sub-goal 2.2: Misuse Prevention The technology should include clear boundaries on acceptable uses, prohibiting deployment in ways that could cause environmental harm, exploit labor, or bypass safety standards. Clear instructions and restrictions reduce the risk of unintended or harmful applications.

Goal 3: Equity and Community Protection: Ethical governance must ensure that benefits are shared fairly and that risks are not disproportionately placed on vulnerable communities.

Sub-goal 3.1: Community-Centered Design Because this application operates in agricultural regions, governance should prioritize engagement with local communities, including farmworkers and families who interact with the land daily. The system should reduce labor burden, not increase risk or surveillance. Sub-goal 3.2: Economic Opportunity and Job Creation The application should be designed to support sustainable job pathways, such as system maintenance, monitoring, and local manufacturing, ensuring that technological advancement contributes to livelihoods rather than displacing workers.

Goal 4: Autonomy, Consent, and Data Stewardship: As the system collects and stores operational and biological data, governance must respect user autonomy.

Sub-goal 4.1: Informed Use and Consent Users should clearly understand what data is collected, how it is used, and how automated decisions are made. Participation should be voluntary, with transparent communication rather than implicit data extraction. Sub-goal 4.2: Responsible Data Governance Data collected by the system should be limited to what is necessary for functionality, securely stored, and not repurposed without consent. This ensures that technological efficiency does not come at the cost of autonomy or trust.

Conclusion

Together, these governance and policy goals ensure that the biological engineering application advances sustainability and innovation while protecting people, ecosystems, and communities. By prioritizing non-malfeasance, safety, equity, and autonomy, the system can contribute to an ethical future where biological engineering serves both environmental stewardship and human well-being, rather than creating new forms of harm or exclusion.

3. Next, describe at least three different potential governance “actions” by considering the four aspects below (Purpose, Design, Assumptions, Risks of Failure & “Success”). Try to outline a mix of actions (e.g. a new requirement/rule, incentive, or technical strategy) pursued by different “actors” (e.g. academic researchers, companies, federal regulators, law enforcement, etc). Draw upon your existing knowledge and a little additional digging, and feel free to use analogies to other domains (e.g. 3D printing, drones, financial systems, etc.). Purpose: What is done now and what changes are you proposing? Design: What is needed to make it “work”? (including the actor(s) involved - who must opt-in, fund, approve, or implement, etc) Assumptions: What could you have wrong (incorrect assumptions, uncertainties)? Risks of Failure & “Success”: How might this fail, including any unintended consequences of the “success” of your proposed actions?

Governance Action 1: Community-Centered Operations and Livelihood Integration

Actors: Farmworkers, families, parents, local community members, growers, community organizations Purpose: What is done now: Agricultural and technological systems often treat farmworkers and families as labor inputs rather than stakeholders in governance. Proposed change: Embed community members—especially farmworkers and families—into the operation and stewardship of the system. Governance begins with livelihoods, ensuring the technology improves working conditions, stability, and long-term opportunity rather than replacing or burdening people. This mirrors how foundational workforce roles support larger systems in aviation and space programs, where ground crews and technicians are essential to mission success Design Systems are designed to be operable and maintainable by local workers. Training pathways are practical, paid, and accessible. Community members participate in identifying risks, needs, and improvements. Government and institutions support job creation and worker protections rather than imposing complex regulatory burdens on individuals.
Assumptions That people closest to the land have valuable operational knowledge. That economic stability supports ethical behavior and safety. That technology adoption increases when communities benefit directly. Risks of Failure & “Success” Failure risk: Community roles become symbolic without real authority. “Success” risk: Increased responsibility without fair compensation. Unintended consequence: Technology may deepen inequality if job quality is not protected.

Governance Action 2: Cross-Sector Engineering and Stakeholder Accountability

Actors: Engineers, technicians, researchers, manufacturers, environmental stakeholders, community representatives Purpose What is done now: Engineering decisions are often siloed within technical or corporate environments, with limited integration of social or environmental context. Proposed change: Create shared accountability between engineers, stakeholders, and affected communities to guide system evolution. Governance here focuses on how the system grows, adapts, and corrects itself over time. This reflects NASA’s model of cross-disciplinary review, where engineers, operators, and safety experts jointly define acceptable risk and system behavior. Design Engineers define technical limits and safeguards. Stakeholders and community representatives provide real-world context. Feedback loops allow system updates based on observed outcomes. Participation is incentivized through funding, procurement, or industry standards rather than enforced solely through regulation. Assumptions That collaboration across sectors improves safety and resilience. That engineers are willing to integrate non-technical input. That shared responsibility reduces blind spots. Risks of Failure & “Success” Failure risk: Coordination slows innovation. “Success” risk: Committees become performative rather than influential. Unintended consequence: Power imbalances may marginalize community voices if not intentionally protected.

Governance Action 3: Structural Evolution Through Public Infrastructure and Workforce Systems

Actors: Government agencies, workforce development institutions, educators, funders, industry partners Purpose What is done now: Government oversight often focuses on compliance after deployment rather than enabling ethical growth beforehand. Proposed change Position government and institutions as infrastructure builders, supporting long-term evolution through workforce pipelines, shared standards, and sustained investment. Governance here focuses on continuity, ensuring systems do not collapse when funding cycles, personnel, or technologies change. This mirrors NASA’s long-term investment in education, standards, and institutional memory to sustain decades-long missions. Design Governments fund training, apprenticeships, and certifications. Institutions translate complex regulations into accessible standards. Public investment is tied to job creation, environmental benefit, and safety. Knowledge transfer mechanisms ensure continuity across generations. Assumptions That public investment can guide ethical outcomes. That stable infrastructure supports innovation better than ad-hoc regulation. That long-term planning outweighs short-term efficiency gains. Risks of Failure & “Success” Failure risk: Programs become underfunded or politicized. “Success” risk: Systems become overly dependent on public funding. Unintended consequence: Institutional rigidity may slow adaptation if feedback loops are weak.

Conclusion

Together, these governance actions reflect an evolutionary model of ethics, similar to those used by NASA and the aviation sector. Governance is achieved not through a single rule, but through community participation, technical accountability, and institutional continuity. By aligning livelihoods, engineering evolution, and public infrastructure, this biological engineering system can grow sustainably while protecting people, land, and future generations

5. Last, drawing upon this scoring, describe which governance option, or combination of options, you would prioritize, and why. Outline any trade-offs you considered as well as assumptions and uncertainties. For this, you can choose one or more relevant audiences for your recommendation, which could range from the very local (e.g. to MIT leadership or Cambridge Mayoral Office) to the national (e.g. to President Biden or the head of a Federal Agency) to the international (e.g. to the United Nations Office of the Secretary-General, or the leadership of a multinational firm or industry consortia). These could also be one of the “actor” groups in your matrix. Reflecting on what you learned and did in class this week, outline any ethical concerns that arose, especially any that were new to you. Then | | propose any governance actions you think might be appropriate to address those issues. This should be included on your class page for this week.

Prioritized Governance Recommendation

Drawing on the scoring above, I would prioritize a combination of Governance Option 1 (Community-Centered Operations and Livelihood Integration) and Governance Option 2 (Cross-Sector Engineering and Stakeholder Accountability), with Governance Option 3 (Public Infrastructure and Workforce Enablement) playing a supportive, longer-term role.

This layered approach reflects the reality that ethical and sustainable systems are not governed by a single rule or actor, but by how people, technology, and institutions interact over time.

Primary Priority: Option 1 – Community-Centered Operations

I would prioritize Option 1 as the foundation because it scored highest in feasibility, minimizing burdens, environmental protection through prevention, and promoting constructive applications. Most importantly, it directly centers farmworkers, families, and local communities as active participants rather than passive recipients of technology.

For agricultural regions, this approach reduces harm by:

Preventing incidents early through lived experience and proximity to the land

Building trust and accountability into daily operations

Ensuring that governance is understandable and accessible to non-experts

This option aligns strongly with equity goals, as it creates jobs, builds local capacity, and embeds ethical responsibility at the point of use rather than relying solely on external enforcement.

Secondary Priority: Option 2 – Cross-Sector Engineering & Stakeholder Accountability

Option 2 is essential to complement Option 1, especially given its strong performance in biosecurity, lab/operational safety, and incident response. While community-centered governance is effective at prevention, complex biological and automated systems also require engineering expertise and shared technical responsibility.

This option ensures that:

Engineers, researchers, and stakeholders jointly define safety limits

Risks are anticipated before systems scale

Accountability is distributed rather than siloed

The combination of Option 1 and Option 2 mirrors successful models in fields like aviation and aerospace, where frontline operators and technical experts continuously inform one another.

Supportive Role: Option 3 – Public Infrastructure & Workforce Enablement

Option 3 scored lower on cost and feasibility but high on long-term response capacity and system evolution. For this reason, I would treat it as a supporting and enabling layer, rather than the primary governance mechanism.

Public investment in workforce pipelines, training, and standards is critical for long-term sustainability, but if prioritized too early or too heavily, it could:

Introduce unnecessary bureaucracy

Increase burdens on communities

Slow innovation

When aligned with Options 1 and 2, however, Option 3 helps ensure continuity, stability, and generational knowledge transfer.

Trade-Offs Considered

Equity vs. speed: Community-centered approaches may move more slowly but produce more durable and just outcomes.

Coordination vs. efficiency: Cross-sector governance requires effort and negotiation but reduces blind spots.

Cost vs. resilience: Public infrastructure investments are costly but provide long-term stability.

Assumptions and Uncertainties

This recommendation assumes that:

Communities want to participate in governance when given real authority and support

Engineers and stakeholders are willing to share responsibility beyond technical performance

Government can act as an enabler rather than a barrier

Uncertainties include:

Long-term funding stability

Power imbalances between technical experts and community voices

How these models adapt as systems scale beyond local regions

Intended Audience

This recommendation is directed toward regional and state-level public agencies, community organizations, and engineering stakeholders operating in agricultural regions. These actors are best positioned to implement layered governance that balances safety, equity, and innovation without over-reliance on top-down regulation.

Conclusion

In summary, prioritizing community-centered governance supported by cross-sector technical accountability, with public infrastructure as a stabilizing force, offers the most ethical, feasible, and sustainable path forward. This approach prevents harm early, distributes responsibility fairly, and allows the system to evolve responsibly—much like successful long-term models in aviation and aerospace.