NEW YORK CITY - LISBON

NEW YORK CITY - LISBON

A Global Network Based in NYC to Study

and Accelerate Artificial Intelligence for All

Our Work

ARCx fosters dialogues, builds international and multidisciplinary teams, and creates knowledge and tools to address the research, educational, methodological, organizational and societal needs necessary for high-impact and ethical AI innovation. We work closely with academics, entrepreneurs, investors, public authorities, civil society and industries. Some of our clients and partners include The City of New York, New Lab, NYC Economic Development Corporation, the New York Academy of Sciences, Columbia University, NYU Gov Lab, Cornell Tech, the Portuguese Parliament, the Municipality of Lisbon, Global Futures Group and the Kazakhstan’s Academy of Public Administration.

Our work follows a six-pillar methodology that allows us to operate in multiple regions of the world at the intersection of multidisciplinary approaches, artificial intelligence, and innovation.

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1: Research & Discover

2: Learn & Evolve

3: Decide & Innovate

4: Deploy & Add Value

5: Evaluate & Improve

6: Disseminate & Impact All

Research & Discover

•  Industry-specific AI Innovation Ecosystem Reports

• Organization-specific AI Innovation Drivers Reports

• AI Algorithms Mapping Reports: Evaluations, Integration, and Governance

• AI Challenges for Business Solutions Scouting with Technology Firms and Academia 

Learn & Evolve

•  Industry and Organization-specific AI Skills and Competencies Audit

• AI Training Paths for Senior Management and AI Technicians

• Customized AI Curricula and Programs

• AI Innovation Trade-offs Report

• AI Talent Mobility Programs

Decide & Innovate

• Participatory and Advisory Roundtables

• AI Innovation Roadmap (Recommendations research, education, and business deployment)

• Data Supply/Demand Map: input data, training data, feedback data

• Organizational Redesign and AI/ML Modeling Report 

Deploy & Add Value

• Advisory Groups and Strategic Partnerships Report

• Stakeholders, Data, AI/ML techniques, Talent and Computational Power Report

• Research and development Collaborative AI Labs: from modeling to deployment 

Evaluate & Improve

• AI Monitoring & Evaluation Framework

• Responsible AI Report: explainability, reliability, value, law, ethics, risks, safety and security 

Disseminate & Impact All

• ​Industry-wide Report

• Organization-specific case studies

• Papers series and Academic Journal

• AI Webinars

• Standards and benchmarks: transparency, fairness and trust

• Podcasts