As artificial intelligence continues advancing rapidly, its applications in the humanitarian sector have significantly increased in recent years. 

AI is now used across various domains, such as the distribution of aid, disaster response and livelihood programs. However, while this powerful technology holds great promise to transform relief efforts, its growth also raises important issues that need addressing. 

Statistics show that over 80% of aid organisations feel that regulations must be revised. Additionally, only sustainable communities globally have access to AI. This will explore the ethical challenges with AI in humanitarian work and potential solutions to ensure it safely achieves its aim of helping the world’s most marginalised people.

Also read: AI in NGOs: Revolutionising the Humanitarian Sector

Recommendations for Ethical AI Governance

As artificial intelligence brings promise and pitfalls, establishing cooperative frameworks for its ethical development is crucial. Key factors include:

Policy Recommendations

Governments and oversight bodies should implement justice, fairness and human welfare frameworks. Comprehensive guidelines address algorithmic accountability, open data practices, and the mitigation of unintended harms. 

Sector-specific policies support high-risk applications in fields like credit scoring or refugee support through transparent auditing. Effectiveness demands durable multi-stakeholder cooperation and accessible grievance mechanisms. 

Regular reviews maintain pace with AI evolutions. When handled judiciously and participatory, governance cultivates confidence and innovation.

Organisational Strategies

Institutions adopt whole-team training emphasising ethics as integral to the design, deploy rigorous impact assessments and vet solutions with oversight panels, including community advisors. 

Roadmaps integrate responsible practices into long-term plans through pilot-and-learn cycles. Leaders champion diversity and inclusion to broaden problem-solving and better identify blindspots. 

Partnerships across sectors optimise skills and resources to scale solutions assisting underserved groups. Documentation and impact reports foster transparency while protecting individual data.

Stakeholder Involvement

Informed civil dialogue is the surest path towards policies acknowledging multifaceted viewpoints. Policymakers consult directly with affected communities to understand place-based concerns shaping legitimate regulation. 

Experts across domains collaborate to solve interdisciplinary challenges. Enterprises provide use cases and regulatory inputs alongside detailed method feedback. 

With open and adaptive collaboration, AI can be developed and governed as a public good benefiting humanity.

Also Read: Challenges of Using Technology for Humanitarian Aid

Challenges

While AI promises to enhance humanitarian assistance, specific challenges must be addressed for the technology to achieve its potential. Many of these barriers are common to other digital transformation sectors, such as data accessibility and quality issues, funding constraints, inclusion concerns, and oversight complexity.

However, the adoption curve for AI within humanitarian organisations currently needs to catch up to that of other industries. This is partly because NGOs operate in crisis settings with limited digital infrastructure and capacities.

Additional obstacles specific to introducing AI techniques include a lack of:

Nascent Understanding Across Humanitarian Sectors

While some humanitarian organisations have begun exploring AI applications and hiring dedicated staff, general comprehension still needs to be improved – particularly among non-technical teams directly assisting communities.

With a sufficient understanding of AI’s potential benefits, organisations can envision impactful use cases or justify strategic investment more quickly. Innovation Consulting & Solutions (ICS) focuses on expanding cross-organisational knowledge through workshops, materials, and expert mentorship to thoughtfully assess AI appropriateness, responsibilities, and opportunities for scaling solutions.

Comprehensive capacity-building initiatives remain crucial to unlocking AI’s promise by cultivating awareness across all operational and support function levels.

Scarcity of Accessible Expertise

Attracting and retaining specialised technical talent to internally drive AI initiatives continues to pose difficulties for cash-strapped non-profits competing with private sector wages.

Even securing short-term pro-bono support introduces compatibility challenges matching time-intensive aid cycles. Onboarding volunteers requires cultural integration without full-time oversight. Non-profit managers also need to gain experience managing technology teams and initiatives.

Innovative solutions are needed to sustain progress, such as dedicated fellowship programs, skill-sharing networks, and optimised in-kind partnerships to establish deeper pools of AI expertise committed to social missions.

Pervasive Data Inaccessibility and Resource-Intensive Processes

High-quality, representative data is core to effective AI/ML but requires more effort to collect and organise with constrained field infrastructure and priorities at a humanitarian scale.

Where information does exist, manually reviewing, labelling and cleaning vast unstructured datasets is prohibitively time-consuming and expensive. These deficiencies impede the pursuit of evidence-based, data-driven approaches essential to enhancing impact.

Creative strategies must streamline the collection and use while upholding participatory standards, leveraging available sources and automating ancillary tasks.

Funding Models Unsuited to Innovation

Traditional philanthropic structures emphasise readily implemented, proven solutions over the experimentation and capacity building required for societal AI deployment.

AI project value also emerges gradually through an iterative process of exploration and learning. Flexible investment supporting expertise retention, data management, and tools over entire program lifecycles has been limited.

New models tolerating risk and slow impact are crucial to cultivating transformational technology for humanity’s most complex problems.

Requirements for Specialised Ethics Guidance

While interest in responsible AI grows, non-profits need assistance conducting risk assessments and operationalising fairness, transparency and community-focused design.

Targeted training, frameworks and advisory services could help systematically evaluate options and safeguard vulnerable populations through all development stages.

Ethics guidance is paramount to ensure AI augments humanitarian work equitably and inclusively, respecting diverse local needs.

Barriers to User-Friendly Tools

Many early efforts depend on time-bound collaborations for model prototyping and deployment support.

Overcoming this requires scaling accessible no/low-code platforms and assistance in integrating suitable solutions into programs independently to maximise sustainable impact beyond initial pilot scopes.

User-centric design embracing varied technical capacities broadens AI’s reach.

Also read: Artificial Intelligence and the Humanitarian Sector

Ethical Considerations

As humanitarian AI expands, key considerations ensure technologies responsibly empower communities through practices like transparency, data security, addressing bias, and upholding human oversight.

Here are some ethical considerations you need to know:

Transparency and Accountability

For AI to enhance humanitarian work without compromising core values, organisations must disclose model capabilities and limitations and identify experts responsible for results.

Communities served deserve explanations of data use and impacts in local languages. Independent oversight ensures accountabilities are upheld should unintended harms occur.

With the well-being of vulnerable groups at stake, transparency throughout development and operations wins vital trust that AI augments rather than replaces human connection.

Data Privacy and Security

Personal profiles collected by well-intentioned technologies like biometric IDs should have robust safeguards against illegal access by state and non-state actors.

Strict controls and encryption minimise the risks of sensitive asylum seeker or victim data being misused for harm. Earning participation means involving communities in custodial protocols that respect local traditions.

Destroying non-essential information as promptly as possible assures individuals of control over digital footprints. Such protective measures show that AI backs up for rights and dignity.

Algorithmic Bias

All involved in data sourcing, annotation, and model refinement must thoroughly screen for historical prejudices within training materials through consultations that acknowledge diverse identities.

Mechanisms identifying and addressing bias help address root causes perpetuating inequitable systems. External audits validate priorities centres assisting people impartially according to needs.

With impartiality core to the mission, humanitarian AI demands vigilance, offsetting even subtle skews that threaten just resource distribution.

Oversight

While technology augments overburdened operations, AI presents dilemmas unique to assisting conflict-affected populations best navigated by seasoned expert managers familiar with local complexities.

Technical capacities amplify human empathy, not supplant it. Mechanisms allowing recourse and prioritising worker discretion ensure technology remains a collaborative tool, not a replacement for relationships essential to protection and empowerment in crisis settings.

Also Read: How Technology Helps in Increasing Humanitarian Aid?

Conclusion

While significant challenges remain regarding responsible and equitable AI development, exploring its applications could expand the scope and impact of humanitarian work.

At Innovation Consulting & Solutions (ICS), we aim to provide superior IT services and solutions for NGOs using cutting-edge technologies, including AI, where appropriate. Through our consulting expertise and customised programs, ICS aims to help organisations overcome on-the-ground issues, optimise operations, and scale assistance efforts.

As the crisis landscape evolves rapidly, we remain committed to accelerating progress in addressing humanity’s most pressing issues through innovative and ethical tech solutions.