Phil van Allen helps imagine, prototype, and realize effective and creative AI driven products, services, ecosystems, and experiences. We invented Animistic Design, giving personality to AI by developing backstories, characters, and POVs.

What We Do
What We Do

Develop new directions with emerging technologies

Emerging technologies like AI have unexpected affordances, limits, ethical implications, and outcomes: to keep pace, you need provocative new visions, tools and methods.

 

  


IDEAS & EXPERIMENTS


 


AI implementations often miss the risks and opportunities. As technologies emerge and evolve, so too must design. Succeed through bold experimentation, critical reflection and challenging the default. Unlock the hidden value of your data and expertise with AI in ways that conventional approaches can't.

Services

Your organization can embrace:

CRITICAL PROTOTYPING

Think through making by sketching prototypes, critically reflecting, and producing new product visions (read more about critical prototyping)

STRATEGY AND ETHICS

Define an ethical strategy for AI that aligns with your brand, values, and mission, while avoiding risky  outcomes

FORESIGHT & INSIGHT

Adapt your plans to emerging technology and trends to invent more successful futures

TRAINING & WORKSHOPS

Equip your creatives, staff, and management with the right expertise to take advantage of AI to make more effective products and services 

NEW OPPORTUNITIES

Develop creative, valuable, and unexpected ways of applying new technologies in your next key initiative

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Still thinking about @philvanallen's new, great #AI-for-#UX-designers toolkit: http://philvanallen.com/portfolio/delft-ai-toolkit/… (think: Lego Mindstorms for AI w/wizard of Oz puppeting as a key component of the workflow)

As designers move from the #design of individual things to complex ecologies of smart things, some older conceptions that influenced the development of #AI may have renewed relevance https://hubs.ly/H0fYHwl0 @mikekuniavsky, @xeeliz and @philvanallen detail in @interactionsMag

Interactions Magazine

“One of the things we have to think about designing for AI is people’s perceptions of AI (i.e. Smart, Social, Inuitive, Alive) In fact, AI is quite dumb. It’s the exact opposite of what people think it is (i.e. Kinda Smart, One POV, Awkward, Very limited, Not alive).” @philvanallen #dwpdx

Artificial Intelligence: “It has to be a designed artifact not just a tech artifact.” @philvanallen Thank you @JLRIncubator for the discussion as part of @DesignWeekPDX.

Phil van Allen has 20+ years of experience with technology, media, innovation, and research

Delft AI Toolkit Robot

FAQ

What are your services?
We help our clients succeed with AI and other advanced technologies. We consult on strategy, foresight, prototyping, and design. Contact Us

What is AI?
We think of AI as Augmented Intelligence. While understanding the potential problems with AI, we believe in using data, design and computation to make humans and organizations smarter.

How do you see foresight?
In a dynamic dialog with Commotion AI, we'll examine your business to discover how future trends in AI may affect your planning.

How do you approach Strategy and Ethics? 
Ethics are key consideration when developing AI driven products or services. Data collection and analysis by AI creates a high potential for invasion of privacy, security risks, bias, discrimination, and the unwanted commercial exploitation of our personal data/activities.

Ethics Further discussion

AI Errors: Machine learning depends heavily on being trained on examples, and if the example data is bad or mislabeled, the system can make serious mistakes. For example, the Google Photos app uses AI to tell you who or what is in your photos. But in a horrible example of racism that comes from bad design, hiring practices, data, and testing, the system started identifying black people as gorillas.

Unintended Bias: AI can unintentionally reproduce the biases of the designers, organizations, cultures that are the context for creating the system. AI can help reduce bias, but it can also bake in and scale bias. — Machine learning depends heavily on being trained on examples, and if the example data is bad or mislabeled, the system can make serious mistakes. For example, the Google Photos app uses AI to tell you who or what is in your photos. But in a horrible example of racism that comes from bad: design, hiring practices, data, and testing, the system started identifying black people as gorillas.

Surveillance: AI can be used to track people both online and IRL, and this tracking info must be secured by the organization responsible for the data (e.g. home security/automation vendors). Another area of concern is facial recognition in public areas, which can be used to identify where specific people are without their permission. For example, a company (Clearview.ai) is currently compiling photos from social media for facial recognition, and selling an app to police, governments, and others so they can identify people within seconds of capturing a photo.

Privacy: AI can notice very subtle patterns, and by analyzing them, can reveal private information. For example, a high school student who shopped at Target started receiving pregnancy related marketing before she had told her parents she was pregnant. This is a classic case of unintended consequences, where the sending of marketing materials both revealed private information and made people feel creepy.

Labor displacement: While AI has the potential to increase satisfaction and decrease the drudgery of work, it also can replace existing workers. For example, autonomous freight trucks may put many truck drivers out of work.

Do you offer training and workshops?
Yes. We can increase your team's effectiveness through hands-on workshops on the essentials of AI and its design.

Who is Phil?
Phil is a long-time innovator, researcher and expert in the design of new technologies.

CONTACT US

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