Christopher Robert

#FundraisingCatalyst | Donors are becoming more outcome-oriented and seeking impact opportunities aligned with their priorities. Leverage Sattva Consulting’s ecosystem knowledge and funder intelligence, powered by FundAssist, to build a market-resilient fundraising strategy that drives stronger conversions. FundAssist is our data-driven solution that assists organisations in identifying funders aligned with their priorities and focus areas. It offers valuable funder insights, backed by information about 37,000+ companies and funders about their CSR priorities, spending habits, and preferred funding model, to ensure that organisations are equipped to engage with the right funders. Contact us at impact@sattva.co.in to learn more. #SattvaFundraisingCatalyst #FundraisingAdvisory #NonProfitAdvisory Arun Nathan | Aarti Krishnan | Smruti Das | Nilav Kumar Pyne | Aishwarya Meena | Phuhaar Goel | Riya Gupta | Apoorva Prabhu

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Maybe you didn't know the world as you know it depends largely on open-source software. This is important for a free and open society that supports innovation and collaboration. And, not to tie everything to AI, but AI software developing agents and assistants exist because they trained on open-source codebases. I'm glad there are humans focusing on this aspect of keeping the world turning.

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2026 federal funding update for ecosystem builders A week ago I wrote about where federal innovation funding stands for 2026. Here's what's changed in 7 days: What's now signed into law: The Commerce, Justice, and Science bill passed the Senate 82-15 on January 15 and is headed to the president's desk. This locks in: NSF → $8.75 billion (with protection against disproportionate cuts to any directorate) → Regional Innovation Engines: Up to $200 million EDA → Tech Hubs: $41 million → Build to Scale: $50 million → MEP: $175 million What passed the House, awaiting Senate action: The Financial Services bill passed 341-79 on January 14, confirming: SBA → Entrepreneurial development: $330 million (Congress rejected the proposed cut to $150M) → Regional Innovation Clusters: $9M → Federal and State Technology Partnership (FAST): $9M → Growth Accelerator Fund Competition: $9M What's still in flux: Leaders just released a final bipartisan package for Defense, Homeland Security, Labor-HHS-Education, and Transportation-HUD. The House may vote this week, with the January 30, 2026 deadline approaching. SBIR/STTR authorization remains expired. No new solicitations until reauthorization—though there's been some movement here. There's also a bunch of new AI policy I need to dig into still. The bottom line hasn't changed: You cannot build a 10-year innovation ecosystem on annual appropriations battles. The regions that succeed are strengthening their partnership infrastructure now, and leveraging federal funding as a bonus to accelerate outcomes. See the full analysis: https://lnkd.in/euDxDVkZ

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As I fly out to San Francisco to attend TrustCon 2025, I wanted to share some thoughts on why Internet Works was started and why its advocacy work is so important. Why Middle Tech Needs a Policy Voice Middle Tech companies — the innovative layer between Big Tech giants and early-stage startups — are the digital economy’s most overlooked powerhouses.  These firms span search, hosting, forums, video-sharing, communication, reviews, media, and more.  They serve millions of users daily, empower small businesses, and bring diversity, competition, and consumer choice to the internet — without the market dominance, vertical integration, or regulatory resources of the largest players.  Yet too often, public policy fails to reflect this diversity.  Regulations crafted to address the scale and practices of market dominant tech companies are frequently applied across the board, regardless of company size, technical capacity, or business model.  This “one-size-fits-all” approach risks undermining the very companies that foster innovation and offer real alternatives for users and businesses alike. Middle Tech companies: Are often the missing middle voice in policy conversations. They are not startups, but not Big Tech either — they include well-established platforms and services that shape the online experience for millions. Operate diverse business models across communications, media, marketplaces, and digital infrastructure. Don’t benefit from economies of scale, extensive legal teams, or policy leverage that Big Tech enjoys. Are disproportionately affected by regulatory complexity, legal uncertainty, and high compliance costs — despite posing vastly different risks. Know how to be pragmatic and solutions oriented, they want digital regulation to succeed. At the end of the day, Middle Tech doesn’t just need to be included in digital policy — it needs to be understood.  These companies operate responsibly, foster trust, and compete fairly, all while navigating a regulatory landscape not built with them in mind. A sustainable internet future depends on policymaking that recognizes the nuance in today’s tech ecosystem.

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Understanding the Impacts of Generative AI Use on Children | WP1 Surveys | prepared by: The Alan Turing Institute The mission of this report is to critically examine the transformative role of generative artificial intelligence on children’s cognitive, social, and educational development, providing evidence-based guidance for policymakers, educators, and caregivers. It seeks to illuminate both the unprecedented opportunities for personalized learning and the emergent risks associated with unregulated exposure, establishing a framework for responsible governance of AI technologies in formative contexts. This investigation is positioned at the intersection of behavioral economics, developmental psychology, and digital ethics, emphasizing strategic foresight in AI integration. The survey findings reveal that children interacting with generative AI exhibit a 14–18% acceleration in problem-solving efficiency and a 12–15% increase in adaptive learning retention relative to traditional learning environments. Notably, structured parental and educational supervision increases cognitive ROI by approximately 16%, while unsupervised exposure correlates with a 9% rise in risk of attention and behavioral disruption. The data further demonstrate that equity in access to AI-enhanced learning tools improves educational resilience by 22% across socio-economic cohorts, signaling critical implications for inclusive policy design. Analysis of these outcomes underscores a nuanced risk-reward calculus. Institutions implementing guided AI usage report ROE improvements of up to 11% in educational outcomes per unit of investment, reflecting both direct learning gains and longer-term socio-emotional benefits. Conversely, unregulated adoption presents measurable downside exposure, including reduced attention spans and early digital dependency, which may depress long-term efficiency by 7–9%. These insights demonstrate that strategic governance, rather than wholesale avoidance, maximizes the net social and financial return of AI interventions for child development. In conclusion, the integration of generative AI in children's learning environments represents a high-stakes frontier of human capital development, where careful calibration of access, supervision, and ethical frameworks can materially enhance cognitive ROI, equity, and systemic resilience. Policymakers and educators are thus tasked with orchestrating AI adoption not merely as a technological upgrade, but as a strategic investment in the next generation, with measurable returns in both individual capability and societal welfare. #GenerativeAI #ChildDevelopment #CognitiveROI #AIethics #EducationalResilience #DigitalGovernance #PolicyInnovation #ResponsibleAI #AIinEducation

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New Executive Order: Improving Oversight of Federal Grantmaking "(iv)  review of funding opportunity announcements and related forms to ensure that they include only such requirements as are necessary for an adequate evaluation of the application and are written in plain language with a goal of minimizing the need for legal or technical expertise in drafting an application;" Not sure how far this will push agencies to simplify the process. AFWERX after a few years of making it easy (slide-decks), recently went back to the traditional written text format for submission. Presumably, text is easier to analyze with AI tools that slide-decks. If the agencies truly want, they can realllyyy help make this super easy and straightforward to attract the best solutions from the applicants... and some non-traditional formats are getting there. However, the flip side that I have heard from the agencies is that they feel it's some kind of filter to have complicated proposal systems to weed out those that may not have as much drive and attention to detail, as may be needed to execute on the proposal's promises... a kind of proxy test. Another argument that I have heard is that easier proposal submission systems means more proposals being submitted, with AI making it easier to write content, and amplifying the numbers even more. The result being a 'burden' on agencies to review a much larger number of proposals. The reviewers are not paid much (if anything) for reviewing these proposals and are doing it for the good of the community, gaining experience and more knowledge about the industry/segments, and other reasons. How far can one push for more reviewers doing a fair job at throughly assessing these submissions? This problem is akin to the issue with peer-review in academic publications, when open-source journals have no limit to how many papers they can publish... the more quality content, the more visibility the journals gets. Agencies and journals could use AI to review proposals too, and then we're left with AI reviewing AI.... such an interesting, complex, and high-stakes problem to solve! Other industries have this issue as well. Would love to know any examples of solutions that seem to be working. One obvious one is to add in layers of downselections, where automation is used in earlier stages and more human when it's down to a few finalists. But that extends timelines. So much to discuss here. https://lnkd.in/g2yDFuc2

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Autonomous Fundraising is moving missions forward. Virtual Engagement Officers (VEOs) are helping fundraising teams go further by unlocking a new layer of capacity. This is the kind of scale, consistency, and meaningful connection that brings more donors closer to your cause. This week’s VEO by the Numbers: •$1,996,613 raised •17,391 donor engagements (as defined by CASE) •12,599 gifts secured •3 planned gifts •3 multi-year gifts •946 donors re-engaged •197 seamless handoffs to human fundraisers This is the most consequential tech in fundraising. Discover what’s now within reach. → https://lnkd.in/ebqtwXBe

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