The Social Memex – Mark Carranza’s Memory Experiment

September 19, 2009

Mark Carranza has been keeping a list of his ideas since 1984. His list has more
than a million entries, with more than 7 million connections between
entries. Although the media window above appears to contain a video of Mark’s talk at QS #3, Mark preferred that MX not be shown yet, so what you see on screen during the sound recording of talk are the faces of some
of us in group, listening with interest. But even without being able to
see the tool in action, Mark’s description is wonderful. Some
highlights: Mark describes his personal workshop as “The institute for
the prevention of design.” His program is DOS software, last updated in 1992. MX
stands for memory experiment, but if you say these letters again and
again you will notice another allusion. Any element in a list of thoughts can be associated with any other element. “I use it as a thought tool,” Mark says.

At last Monday’s meeting, Mark gave us a quick update on the MX project. Since Esther Dyson was sitting nearby, he went back into his notes and in an instant could recount every time he had heard Esther talk, and what she had talked about. From the look on her face, it seemed that Esther’s memories were being activated by this exercise, too.

Below are Mark’s complete notes from the meeting. I am using them to construct my own account of what happened, and finding them marvelously helpful. The key, for me, in appreciating this experiment, is to understand that these notes are memory aids. They are not meant to stand alone as a story about what happened. Rather, their magic lies in stimulating a chain of associations that bring the older train of thought to mind, updating it in the process. This is working for me after a week has passed, and it seems to work for Mark after years have passed. If you were at the most recent Show&Tell, go ahead and review Mark’s notes and see if they work for you.

talk: Atilla Csordas: rookie coder gene transmission: QS #8; Monday, September 14, 2, 2009

1) 5:52 pm
2) 9/15/09
3) meetup: Quantified Self #8: IFTF: Monday, September 14, 2009
4) accelerating change
5 a pet project
6 open social network
7 XY.0
8 23 and me
9) to access that data
10 to access that data from your phone
11 when you share your genome
12 when you share your genome with others
13 5 Mb text file
14 a 5 Mb text file
15 600,000 rows
16 a rookie coder
17 biosnippet
18 to build a twitterbot
19 building a twitterbot
20 twitter as a real-time search engine
21 searching sequences
22 searching nucleotide sequences
23 searching nucleotides
24) nucleotide sequences
25 twitterbot
26 the constraints can give us creativity
27 how many accounts did you create?
28 twitter spam filters
29 twitter whitelist
30 a low barrier of entry
31 SMS gateways
32 it’s a pet project
33 Atilla
34) following me
35 following my chromosome
36 #chromosome
37 SMS as a low barrier
38 grassroots action
39 tweet what you eat
40 pet gene
41) cell phone



talk: Gopal: memory practice: QS #8: Monday, September 14, 2009

1) 7:42 pm
2) 9/14/09
3 talk: Gopal: extreme cognitive enhancement: QS: March 31, 2009
4) QS talks
5) meetup: Quantified Self #8: IFTF: Monday, September 14, 2009
6 much intuition
7 the source of much intuition
8 the source of much intuition is introspection
9 the facts of memory
10 the internal sight
11) gopal
12) mnemonic techniques
13 your ability to visualize
14 the memory championship
15 what have you learned?
16 speed of recollection
17 accuracy of recollection
18 they’re tracking their eyes
19 your gaze doesn’t move at all
20 eye movements during memorization
21 eye movements during recall
22 eye movement during recall
23 the eye movement during recall video
24 the NLP ‘eye movement during prompted recall’ video at the CIIS class
25 to improve working memory
26) working memory
27 simple training tasks
28 dual and back
29 improving working memory
30 press the space bar
31 practicing the task
32 performance on IQ tests
33 memori loci
34 memory loci
35) extreme cognitive enhancement
36 cognitive enhancement
37 what if you simply studied IQ tests?
38) IQ tests
39) IQ test
40 IQ test performance



talk: Sri: facet of life: QS #8: Monday, September 14, 2009

1) 8:51 pm
2) 9/15/09
3 meetup: Quantified Self #8: IFTF: Monday, September 14, 2009
4 I quit my job
5 my pain is this much
6 I wasn’t disciplined enough
7) I was lazy
8 we stole it
9 the interesting part
10 we stole the name
11 the words you typed in the comments
12 forcing me to log it
13 it’s texting you
14 some kind of intelligent algorithm
15 a comment on the blog
16 to draw conclusions from self-tracking
17 when the self-tracking has a negative cast
18 it’s all self-generated
19 did you talk to your doctor?
20) pain
21 Stanford Pain Clinic
22 facet of life
23 facet of life website
24) SRI
25) that kind of data



talk: Bill Jerrold: speech analysis: QS #8: Monday, September 14, 2009

1) 8:55 pm
2) 9/15/09
3) meetup: Quantified Self #8: IFTF: Monday, September 14, 2009
4) Bill Jerrold
5) speech analysis
6) QS talks
7 someone who likes to do it
8 automated speech analysis
9 to harness your speech
10 untapped information
11 automated speech recognition
12 automatic speech recognition
13 your speech
14) your voice
15 your speech carries a lot of information
16 J. B. Pennebaker
17 poets that commit suicide
18 poets that don’t commit suicide
19 poets that didn’t commit suicide
20 poet-suicide data
21 poet-suicide correlation
22 poetry-suicide correlation
23 the frequency of first person words
24 the higher frequency
25 the higher the frequency
26 the higher the frequency of first person words
27 the sad word frequency
28 sad word frequency
29 sad words
30 clinical feature
31) social feature
32) a social feature
33 male speech
34 female speech
35 male speech/female speech
36 social words
37 social processing
38 correlation despite errors in data
39 correlation despite noisy data
40) UC Davis
41) SRI
42 happy word frequency
43) happy words
44) NLP
45) natural language processing
46 when your computer says, “hey, you’re depressed! :)”
47 “You are cognitively impaired.” OK, Cancel
48 fewer social words
49 deceptive speech
50 characteristics of deceptive speech
51 words associated with the self
52 fewer words associated with the self
53 deceptive speech uses fewer words associated with the self
54 deceptive speech has more positive words and uses fewer words associated with the self
55) Snowden
56 low idea density
57 idea density
58 a lower idea density
59 measuring idea density
60 essays written by nuns
61) nuns
62 an essay written by a nun
63 an educated reader
64 Alzheimer’s
65 nuns with Alzheimer’s
66 the number of prepositions
67 the number of propositions
68 the number of prepositions/the number of propositions
69 many other findings
70 cognitively normal
71 referential failure
72 literary forensics
73) language features
74) a famous example
75 book: True Colors
76 forensicist
77 literary forensicist
78) the Clinton Administration
79 more dominant
80) dominance
81 dominance measure
82) UCSF
84 an approach which is completely automatic
85) laboriously
86 laboriously go over it
87) tagged data
88 to laboriously go over it
89 laboriously, laboriously, laboriously
90 laborious, laborious, laborious
91 the scale of these kinds of studies
92 look for new patterns
93 machine learning
94) David Rumelhart
95) Rumelhart
96 some disease
97 some neurological disease
98 some rare neurological disease
99 some rare aphasia
100 aphasia
101 semantic dementia
102) dementia
103 dementias
104 semantic dementias
105 this speech recognition
106 8:01 pm
107 negative emotion words
108) disfluencies
109) disfluency
110) emotion words
111 positive emotion words
112 negative emotion words/positive emotion words
113 positive emotion words/negative emotion words
114 its accuracy
115 guessing at random
116 a lot of the speech was slurred
117 average word error rate
118) word error rate
119 high word error rate
120 high word error rates
121 pretty high word error rates
122 the Western Aphasia Battery
123 to describe a picnic scene
124 to establish rapport
125 the answer seems to be yes
126 the answer seems to be: yes
127 an answer that seems to be yes
128 ambient speech
129 ambient speech samples
130 a set of recordings
131 what is my impression of this?
132 what is my impression of this talk?
133 the purpose of this study
134 relationships between personality and heart disease
135 a question that was self-focused
136 are you satisfied by all the events in your life?
137 the two distributions
138 some of these effects
139) to gain insight
140 to gain insight into ourselves
141 spontaneous speech
142 people who aren’t older adults
143 people who aren’t old
144 decent diagnostics
145 frequency profile
146 frequency profiles
147 if you’re experimenting with something
148 we need tagged data
149 every phone conversation
150 how good I felt
151 how happy I felt
152 people who are willing to do a lot of work yourself
153 people who are willing to do a lot of work themselves
154 people who are willing to do a lot of work
155 people who are willing to do a lot of work on their own
156 automated scanning
157 automated scanning of telephone conversations
158 the garage experimenter
159 taking a classifier
160 taking a classifier and repurposing it
161 diary speech
162) speech
163) speech processing
164) speech production
165) speech perception
166 automated speech perception
167 another hope
168 patterns we can’t fake
169) biometrics
170 speech biometrics
171 murdered poets
172 favorite murdered poets



talk: Esther Dyson: 23 and Me: QS #8: Monday, September 14, 2009

1) 8:38 am
2) 9/16/09
3) meetup: Quantified Self #8: IFTF: Monday, September 14, 2009
4) many eyes
5) Esther Dyson
6 do a demo
7 to be brief
8 percent similarity
9 some kind of no-op
10 nigerian person
11 people who aren’t related
12) my brother
13) my sister
14 23 chromosomes
15) 23andme
16 fully identical
17 some of the same sequences
18 the ancestry painting
19 a typical pattern
20 what do you have that is useful?
21 getting more involved with your-self understanding
22 different genomic regions
23 genomic
24) gene
25) gene sequencing
26 semi-private gene sequencing
27 much lumpier similarities
28 owning their own sets
29 if you’ve done anything interesting
30 a social network platform
31 your genome is the slowest changing thing
32 your genome is the slowest changing thing about you
33 a bunch of surveys
34 people who are benefactors
35) benefactors
36 connecting to medical records
37 disease groups
38 going after disease groups
39 in a way that was meaningful
40 to have that data manipulated
41 people need to trust us
42 you can’t de-identify people
43 privacy nuts
44 ethnic person
45 unidentified person
46) talk: Esther Dyson: social networking: Sunday, June 6, 2004
47 that kind of data
48 a threaded narrative
49 mystical scariness
50 by the health system
51 genetic non-discrimination
52 getting them to pay
53 getting them to pay for what happened
54 getting insurance companies to pay for what happened
55 it’s not disclosed
56 if your behavior can change by knowing



talk: Joe Belesqua: passive quantification: QS #8: Monday, September 14, 2009

1) 8:53 am
2) 9/16/09
3 iphone app
4 other dreams I have
5 things that are kind of boring
6 when I measure certain things
7 when I measure certain things, it changes my relationship with them
8 if I had less relationship to this process
9 if I had less relationship to the process
10 if I had less relationship to the process of record-keeping
11) a step function
12 a bed scale
13 a different step function
14) it knows
15 the bed knows
16 it knows what your weight is
17 lots of automatic data collection
18 automatic data collection
19 baby weighing scale
20 baby weighing scales
21 what force needs to be applied to vibrate the body
22 determining mass in low gravity
23 determining mass in zero gravity
24 what force needs to be applied
25 force needs to be applied
26 personal instantaneous feedback
27 greed for tools
28 unpleasant correlations
29 a trailing record
30 don’t suspend your bed with bungee cords
31) meetup: Quantified Self #8: IFTF: Monday, September 14, 2009



talk: Bo Adler: walking data self-guinea pig: QS #8: Monday, September 14, 2009

1) 9:09 am
2) 9/16/09
3) meetup: Quantified Self #8: IFTF: Monday, September 14, 2009
5) Fujitsu
7 data-driven health care
8 cots sensors
9 it goes red
10 you have to get used to wearing it
11 I’m a walking experiment
12 I’m not sure what you’re asking me
13 to synchronize them
14 to synchronize that
15 how accurate the devices are
16 when I’m all wired up
17 sleep apnea
18 could I tell?
19 I would do my own experiments
20 the apnea events
21 the twitter stream
22 I use a regular language
23 what you do with it
24 pulse-ox
25 it doesn’t feel like it helps
26 graphs from the data
27 big variability
28 the first thing I learned
29 it felt like it made a big difference
30 nyquil
31 sudafed
32 benadryl
33 antihistamines
34 it would relax the muscles
35 it’s kind of the same
36 what is the data saying?
37 almost the same
38 a sleep apnea person
39 the sleep apnea guy
40 check your neighborhood
41 circadian rhythm
42) circadian rhythms
43 the heart rates
44 the sleep apnea club
45 data tracking
46 painfully evil
47 the csv files
48 to grab the csv files
49 to grab the realtime data
50) dashboard
51 dashboard-style software
52 to last about a week
53) batteries
54 the number of batteries
55 a green sensor
56 rechargeable batteries
57 [private: email]
58 Bo Adler: [private: email]
59 everybody’s got their own little systems here
60 I’ll try to link to it
61 finding time for everything is hard


These are the notes I took at the 8th Quantified Self Meetup, Monday
night, September 14, 2009.  I wrote them paper at the meetup, then
entered them into my e-memory system MX a day or two after.  I hope
sharing them helps people re-encounter, re-think, at least some of the
great ideas shared there.

For those interested, Gordon Bell and Jim Gemmel will be presenting
their new book ‘Total Recall: How the E-Memory Revolution Will Change
Everything’ at PARC Forum in Palo Alto, next Thursday, September 24,
2006 from 4 to 5pm.  Details at:

The “)” after a number marks entries already in the system when added to a list.

each individual list here, 75% to 87% are new entries, thoughts never
enetered before.  Over all the lists in this set, 85% of the entries
are new.

Each entry on a list is itself a list, a link to the list of which
it is the title.  It’s trememdously important that every connection is
a cross-link.  For example, #31 on the first list is shown as a list,
on which the first list is #3.  I’ve also included from the first list,
lists there numbered: 32, 33, 34, 37, 38, 39.  These are all the talks
except mine and then unfortunately Steve Brown’s after.

Comments and additions welcome to:
or (same thing, really 🙂

Please forgive the software not being ready to release where these lists are active.  Thanks!

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