Monthly Archives: June 2018

QCon 2018 – Rethinking HCI with Neural Interfaces

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Title: Rethinking HCI with Neural Interfaces
Speaker: Adam Berenzweig @madadam

See the table of contents for more blog posts from the conference.

Minority Report analysis

  • why need gloves to interface
  • ergonomics – tiring to hold arm up

History of UI Paradigm Shifts

  • Command line – we still use the command line; just not exclusively
  • mouse, graphics – original Apple. Design innovation; not just tech
  • minesweeper and solitaire built in so could learn how to use the mouse – right click for minesweeper and click/drag for solitarire
  • MIT wearable computing in 1993 paved way for Google Glass. [but successful]
  • Joysticks, gloves, body (Kinect), eye tracking, VR/AR headsets
  • Had audience raise hand if wearing a computer. Not many Apple watch people in the room
  • Future: tech is always there. It knows about the world around you and is always ready

Book recommendation: Rainbow’s End – an old man gets rejuvenated (or something) and comes back younger needing to learn new tech

Intro to Neural Interfaces

  • Interfaces devices to translate muscle movement into actions
  • Human input/output has high bandwidth compared to typing or the like. We think faster than we can relay information. Output constrained.
  • Myo – For amputee, arm where have electrode on arm that controls arm.
  • Neural interfaces have information would have sent to muscle or physical controller
  • Lots of stuff happens in the brain, but you don’t want all of it. You want the intentional part without having to filter out everything else. The motor cortex controls muscles so represents voluntarily control. Also don’t have to plan electrodes on brain.

Examples

  • Touch type without keyboard presence [not very practical as it is hard to touch type without seeing keys]
  • Mirrors intention of moving muscles even if physical attempt is blocked
  • VR/AR – more immersive experience

Designing for Neural Interfaces

  • Want to maximize control/minimize effort
  • Cognitive limits – what can people learn/retain
  • Mouse is two degrees of freedom, laser pointer is three. There is also six where control in space. Human body has ore than six degrees of freedom. Are humans capable of controlling an octopus
  • How efficient is the input. Compared to existing control devices
  • It is possible to control three cursors at once, but it is exhausting. Not a good design
  • Different people find different things intuitive. Which way is up?
  • Don’t translate existing UIs. Can evolve over time.

My take

Fun! Great mix of pictures, videos and concepts. I learned a lot. Would be interesting to see this vs the privacy/ethics track. Imagining what data it could have reading your mind/muscles.

QCon 2018 – Data, GDPR & Privacy

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Title: Data, GDPR & Privacy – Doing it right without losing it all
Speaker: Amie Durr

See the table of contents for more blog posts from the conference.

Goals: send right message to right person at right time using right channel (ex: email, text, etc)

One company handles 25% of all non-spam email traffic

Confidence

  • We don’t trust brands with personal information. 2/3  overall. Nobody in room.
  • Employees at GDPR  compliant companies also don’t believe their company is

Recent thefts

  • Ticketfly – emails and hashed passwords.   Shut down their website
  • Panera – email, name, phone, city, last 4 digits of credit card number
  • MyHeritage – email and hashed passwords
  • Myfitnesspal – name, weight, etc

Need to consider

  • What do you store?
  • For how ong do you store it?

Data and privacy regulations

  • CASL
  • CAN-SPAM
  • Privacy Shield – for data leaving Europe
  • GDPR – EU
  • Future: Germany, Australlia, South America
  • Not about specific regulations. Need to care about data an privacy. Part of   Brand. Customers will leave

Supply for data scientists far exceeds supply

Build trust without stiffling innovation

  • accountability – what do with data, who responsible, continuing to focus on data perception,  audit/clean data, make easy to see what data  have and how opt out/delete
  • privacy by design – innovate without doing harm, don’t want to get hacked, be user centric, move data to invididual so no storing, what is actually PII vs what feels like PII. Anonymize both

Remember user data. If the user types it in, could be anything in here

What they did

  • dropped log storage to 30 days. Have 30 days to comply with requests to delete data. So  handled by design for log files
  • hash email recipients
  • Remove unused tracking data
  • Communicated with customers
  • Kept anonymized PII data, support inquiries, etc
  • some customers feel 30 days is too long so looking at going beyond law

Can delete parts of data vs everything (ex:: stack overflow)

brand and pr vs actually keeping user safe [like what happened with accessibility and section 508]

My take

Good talk. I liked the level of detail and concrete examples. I would have liked a refresher of GDPR. But there was enough to tell me what to google. That helped with what didn’t know (or forgot).

 

QCon 2018 – Privacy Ethics – A Big Data Problem

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Title: Privacy Ethics – A Big Data Problem
Speaker: Raghu Gollamudi

See the table of contents for more blog posts from the conference.

GPDR (General Data Protection Regulation) – took effect May 25, 2018

Data is exploding

  • Cost of storing data so low that it is essentially free
  • 250 petabytes of data a month. What comes ater petabytes?
  • Getting more data when acquire other companies
  • IOT data is ending up in massive data lakes

Sensitive information – varies by domain

  • Usernames
  • user base – customers could be sensitive for a law firm
  • location – the issue with a fitness tracker identifing location of a military base
  • purchases – disclosing someone is pregnant before they tell people
  • employee data

changes over time – collecting more data after decision made to log

Privacy vs security

  • privacy – individual right, focus on how data used, depends on context
  • security – protect information, focus on confidentiality/accessibility, explicit controls
  • privacy is an under invested market. Security is more mature [but still an issue]

Solutions

  • culture
  • invest more – GDPR fines orders of magniude higher than privacy budget
  • include in perormance reviews
  • barrier to entry – must do at least what Facebook does if in that space
  • security – encrypt, Anonymization/pseudonyization, audit logs, store credentials in vault
  • reuse – use solutions available to you
  • design for data integrity, authorization, conservative approach to privacy settings
  • include privacy related tasks in sprint
  • design in data retention – how long do you need it for
  • automation – label data (tag/classify/confidence score)   So can automate compliance. Score helps reduce false positives

EU currently strictest privacy policy  Germany and Brazil working on. There was a debate on whether it applies to EU citizens or residents. Mostly agreement that physical location matters

My take

I was expectng this to be more technical. There was a little about the implications of big data like automation. But it felt glossed over. I would have liked to see an example of some technique that involves big data. The session was fine. It covered a lot of areas in passing which is a good opening session – lets you know where to plan. I think not having the “what you will learn” session on the abstract made it harder to know what to expect. Maybe QCon should make this mandatory?