Latest / Keeping Up With Reality / The Algorithmic Self

Transcript

The Algorithmic Self · Keeping Up With Reality

• 0:00
  Speaker 1: Precisely 11 45 on a humid thursday evening inside a
• 0:03
  Speaker 1: dimly lit bedroom where the only light source was the
• 0:05
  Speaker 1: cold pale glow of a handheld glass screen a 30
• 0:08
  Speaker 1: year old user interface developer named nathan sat curled under
• 0:11
  Speaker 1: his duvet nathan's thumb was executing its thousands of times
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  Speaker 1: daily upward flick across the glass surface he was not
• 0:19
  Speaker 1: looking for specific news searching for a solution to a
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  Speaker 1: practical problem or communicating with any of his real world
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  Speaker 1: friends He was simply feeding his neurological attention directly into
• 0:29
  Speaker 1: a complex mathematical recommendation model hosted on a cluster of
• 0:32
  Speaker 1: high-performance servers 3,000 miles away. As Nathan scrolled, the algorithm
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  Speaker 1: executed billions of predictive calculations per second. It analyzed the
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  Speaker 1: exact millisecond duration he lingered over a short video of
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  Speaker 1: a dog attempting to catch a frisbee, the precise pressure
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  Speaker 1: of his thumbtap when he liked a photo of a
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  Speaker 1: minimalist mechanical keyboard, his geographic coordinates, the ambient room lighting
• 0:54
  Speaker 1: detected by his device sensor, and his historical scrolling speed
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  Speaker 1: at late hours. Within less than a second, the algorithm
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  Speaker 1: determined that Nathan was currently experiencing a subtle, unexpressed wave
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  Speaker 1: of existential restlessness coupled with mild physical exhaustion. To maintain
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  Speaker 1: his gaze for another 20 minutes, the system bypassed 300,000
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  Speaker 1: potential content items and delivered a precise, custom-curated sequence, a
• 1:16
  Speaker 1: six-second video of an artisan woodworker restoring an oak table,
• 1:20
  Speaker 1: followed by a dramatic 40-second commentary clip about real estate inflation,
• 1:24
  Speaker 1: followed immediately by an advertisement for a high-end ergonomically designed
• 1:27
  Speaker 1: lumbar cushion that claimed to relieve lower back pain for
• 1:29
  Speaker 1: digital workers who sit for more than eight hours a day.
• 1:34
  Speaker 1: Nathan paused on the cushion advertisement. He looked at the
• 1:38
  Speaker 1: sleek foam contours, the breathable mesh fabric, and the graphic
• 1:41
  Speaker 1: illustration depicting a spine shifting from bright red to calming blue.
• 1:45
  Speaker 1: He felt a sudden, acute awareness of a dull ache
• 1:47
  Speaker 1: sitting in his lower back, an ache he had not
• 1:49
  Speaker 1: noticed five seconds prior. Without consciously processing how he had
• 1:53
  Speaker 1: arrived at this decision, Nathan tapped his thumb against the screen,
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  Speaker 1: authorized a digital payment of $ 68, and completed the purchase.
• 2:01
  Speaker 1: He set the glowing rectangle on his nightstand, closed his eyes,
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  Speaker 1: and lay back in the dark. He felt a strange,
• 2:07
  Speaker 1: quiet sensation floating through his mind, the realization that the
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  Speaker 1: software running on a distant server farm knew what his
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  Speaker 1: body needed, what his mind desired, and what his mood
• 2:16
  Speaker 1: required far better than he did. He was no longer
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  Speaker 1: a self-directed human being possessing independent taste, organic desires, and
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  Speaker 1: spontaneous thoughts. He had been quietly, systematically re-engineered into an
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  Speaker 1: algorithmic self, a biological peripheral device attached to a global
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  Speaker 1: predictive data engine. This quiet, midnight transaction in a suburban
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  Speaker 1: bedroom captures the ultimate frontier of modern existence, the total
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  Speaker 1: outsourcing of human agency, taste, and identity to mathematical predictive models.
• 2:44
  Speaker 1: If you examine the history of human decision-making through a
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  Speaker 1: philosophical lens, the fundamental definition of human consciousness was always
• 2:51
  Speaker 1: rooted in agency. To be human meant navigating the difficult, messy,
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  Speaker 1: and often confusing territory of personal choice. You decided what
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  Speaker 1: books to read by browsing physical library shelves or taking
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  Speaker 1: recommendations from local friends. You decided what music to listen
• 3:07
  Speaker 1: to by wandering through record shops, talking to radio DJs,
• 3:11
  Speaker 1: or listening to garage bands perform in local venues. You
• 3:14
  Speaker 1: decided what career path to pursue through trial, error, personal mentorship,
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  Speaker 1: and internal soul searching. Your choices were often imperfect, inefficient,
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  Speaker 1: and slow. You bought terrible albums, read boring books, made
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  Speaker 1: poor financial decisions, and went on awkward dates. But those
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  Speaker 1: very mistakes, inefficiencies, and random discoveries were the precise crucibles
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  Speaker 1: through which your unique character, personal taste, and authentic selfhood
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  Speaker 1: were forged. Over the past two decades, modern technology executed
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  Speaker 1: the most radical psychological trait in human history. It offered
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  Speaker 1: to eliminate all friction, risk, and inefficiency from decision-making in
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  Speaker 1: exchange for total cognitive surrender. We were promised that predictive
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  Speaker 1: algorithms would make our lives infinitely easier. They would filter
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  Speaker 1: out the noise, curate our media, suggest our products, pick
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  Speaker 1: our romantic partners, navigate our traffic routes, and predict our
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  Speaker 1: personal desires before we even felt them. We willingly handed
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  Speaker 1: over our choices to the data models, celebrating the slick
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  Speaker 1: convenience of never having to search, evaluate, or choose again.
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  Speaker 1: We failed to realize that when you outsource the act
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  Speaker 1: of choosing, you quietly destroy the capacity for selfhood. Consider
• 4:23
  Speaker 1: the profound transformation of human taste in the era of
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  Speaker 1: the algorithmic recommendation engine. In previous decades, developing personal taste
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  Speaker 1: in art, music, literature, or film was an active, high-effort
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  Speaker 1: human pursuit. It required curiosity, patience, and a willingness to
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  Speaker 1: explore uncomfortable or challenging territory. You had to actively search
• 4:43
  Speaker 1: out obscure independent record labels, read long literary essays, or
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  Speaker 1: spend hours talking with passionate clerks in specialty shops who
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  Speaker 1: pushed you outside your comfort zone. Taste was a personal signature,
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  Speaker 1: a distinct, highly idiosyncratic collection of artistic loves and hates
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  Speaker 1: built over a lifetime of active exploration. Today, personal taste
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  Speaker 1: has been replaced by the algorithmic stream. When you open
• 5:05
  Speaker 1: a digital music platform, a streaming video service, or a
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  Speaker 1: digital bookstore, you are no longer presented with a wild,
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  Speaker 1: chaotic universe of artistic creation to explore. You are presented
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  Speaker 1: with a hyper-personalized, algorithmically smoothed feed designed specifically to confirm
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  Speaker 1: your existing preferences and keep your attention locked at a
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  Speaker 1: baseline level of passive comfort. The algorithm does not want
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  Speaker 1: to challenge you, shock you, or force you to wrestle
• 5:28
  Speaker 1: with complex, unfamiliar artistic forms. Challenging content creates cognitive friction.
• 5:35
  Speaker 1: Cognitive friction causes users to pause, reflect, and potentially close
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  Speaker 1: the application. Instead, the predictive engine feeds you variations of
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  Speaker 1: what you have already consumed. If you listen to three
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  Speaker 1: quiet acoustic guitar tracks on a rainy Tuesday, the algorithm
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  Speaker 1: will quietly construct a personalized playlist containing 400 nearly identical
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  Speaker 1: quiet acoustic guitar tracks recorded by different artists using the
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  Speaker 1: exact same production values. This dynamic has birthed a distinct
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  Speaker 1: cultural phenomenon, the flattening of global aesthetic variety. Across streaming
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  Speaker 1: music platforms, video networks, fashion retail apps, and interior design hubs,
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  Speaker 1: culture has begun to homogenize into a smooth, frictionless, universally
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  Speaker 1: palatable gray paste. Music production has been optimized for short
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  Speaker 1: attention spans and background listening, featuring identical structural hooks, compressed
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  Speaker 1: dynamic ranges, and predictable rhythmic patterns designed to avoid scaring
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  Speaker 1: away playlist listeners. Interior design trends across global cities have
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  Speaker 1: collapsed into identical minimalist beige aesthetics, engineered to look appealing
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  Speaker 1: in 2-inch digital thumbnail images. We are living in an
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  Speaker 1: era of algorithmic monoculture, where millions of unique human minds
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  Speaker 1: across the globe are fed the exact same mathematically optimized
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  Speaker 1: aesthetic porridge, mistaking the continuous consumption of personalized data for
• 6:49
  Speaker 1: the exercise of personal taste. Consider the staggering transformation of
• 6:54
  Speaker 1: human romantic choice through algorithmic matching engines. For thousands of generations,
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  Speaker 1: human attraction was an organic, mysterious, multisensory phenomenon that defied
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  Speaker 1: simple rational explanation. You fell in love with someone not
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  Speaker 1: because they met a 20-point checklist of demographic metrics, but
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  Speaker 1: because of an unscripted, chaotic spark of physical chemistry, the
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  Speaker 1: way their eyes wrinkled when they laughed, their unique vocal timbre,
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  Speaker 1: their spontaneous sense of humor, or the strange, inexplicable way
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  Speaker 1: your two nervous systems synchronized in a shared physical room. Today,
• 7:24
  Speaker 1: modern dating platforms have reduced the sacred complexity of human
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  Speaker 1: romance to a predictive data-matching problem. Users are instructed to
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  Speaker 1: input their geographic radius, age parameters, income preferences, hike requirements,
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  Speaker 1: and political classifications into a central database. The algorithmic engine
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  Speaker 1: processes these variables, compares them against millions of other user profiles,
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  Speaker 1: and presents a curated queue of potential partners calculated to
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  Speaker 1: yield high compatibility scores. What makes this system so deeply
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  Speaker 1: comedic and tragic is that human romantic chemistry is fundamentally non-algorithmic.
• 7:58
  Speaker 1: A predictive mathematical model can match two people based on
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  Speaker 1: shared demographic metrics, shared interests in indie rock bands, and
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  Speaker 1: identical dietary preferences. But it cannot predict whether those two
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  Speaker 1: people will experience a spark of authentic physical connection when
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  Speaker 1: they sit across from one another in a noisy restaurant.
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  Speaker 1: When the algorithmically matched couple inevitably sits down for their
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  Speaker 1: first real-world date, they often experience a bizarre, sterile disconnect.
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  Speaker 1: On paper, according to the data metrics, they are 94% compatible.
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  Speaker 1: In physical reality, sitting across a small wooden table, the
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  Speaker 1: conversation feels heavy, forced, and completely devoid of organic magic.
• 8:36
  Speaker 1: Instead of recognizing that human attraction cannot be calculated by software,
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  Speaker 1: users assume that the algorithm simply needs more data points.
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  Speaker 1: They return home, update their profile settings, answer 40 additional
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  Speaker 1: diagnostic survey questions, and demand that the machine fetch them
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  Speaker 1: a better match, completely oblivious to the fact that they
• 8:53
  Speaker 1: have converted the profound mystery of human love into an
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  Speaker 1: e-commerce sorting exercise. Consider the pervasive modern phenomenon of algorithmic
• 9:00
  Speaker 1: cognitive echo chambers and reality fragmentation. Because predictive algorithms are
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  Speaker 1: programmed to maximize engagement, they quickly discover that the most
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  Speaker 1: effective way to keep a user glued to a digital
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  Speaker 1: screen is to continuously confirm their existing worldviews, anxieties, and
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  Speaker 1: political biases. If an individual displays a subtle interest in
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  Speaker 1: a specific political perspective, an alternative health philosophy, or an
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  Speaker 1: obscure historical theory, the algorithm immediately begins filtering out opposing viewpoints,
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  Speaker 1: dissenting evidence, and broader contextual information. It constructs a customized
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  Speaker 1: digital reality where every news story, commentary video, and expert
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  Speaker 1: opinion served to the user validates their specific bias. Within
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  Speaker 1: six months of this continuous data feeding, the individual is
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  Speaker 1: living in a completely custom-built reality bubble. What renders this
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  Speaker 1: dynamic so profoundly dangerous to human society is that millions
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  Speaker 1: of individuals living in the exact same physical city are
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  Speaker 1: now operating with an entirely different algorithmically constructed facts when
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  Speaker 1: two neighbors meet on a sidewalk they are no longer
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  Speaker 1: just disagreeing on political policies or cultural opinions they are
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  Speaker 1: inhabiting two completely different cognitive universes generated by two distinct
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  Speaker 1: mathematical recommendation models they look at one another not as
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  Speaker 1: fellow citizens with different perspectives but as brainwashed irrational aliens
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  Speaker 1: who are completely blind to obvious truth The algorithm has
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  Speaker 1: successfully weaponized our natural confirmation bias, converting public discourse from
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  Speaker 1: a shared human conversation into a chaotic war between localized,
• 10:28
  Speaker 1: hyper-personalized reality bubbles. Consider how the algorithmic self has altered
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  Speaker 1: our relationship with human intuition and internal decision-making. Historically, when
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  Speaker 1: a human being faced a complex life choice, whether to
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  Speaker 1: change careers, relocate to a new city, end a relationship,
• 10:44
  Speaker 1: or embark on a creative project, they relied on a
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  Speaker 1: combination of rational analysis, advice from trusted mentors, and a quiet,
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  Speaker 1: deep internal signal known as intuition or gut feeling. Intuition
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  Speaker 1: was the subconscious brain's capacity to synthesize thousands of subtle
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  Speaker 1: life experiences, emotional memories, and bodily sensations into a clear
• 11:02
  Speaker 1: internal compass. Today, we have systematically trained ourselves to distrust
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  Speaker 1: and ignore our internal compass in favor of external data metrics.
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  Speaker 1: If a person feels tired on a afternoon, they do
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  Speaker 1: not listen to their body's natural exhaustion, they check their
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  Speaker 1: smartwatch score to see if the device confirms that their
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  Speaker 1: readiness index is low. If an individual enjoys a meal
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  Speaker 1: at a local restaurant, they hesitate to declare it good
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  Speaker 1: until they check the online review score to ensure that
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  Speaker 1: thousands of strangers agreed with their sensory experience. If a
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  Speaker 1: creator drafts a personal essay, they do not evaluate its
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  Speaker 1: emotional honesty or artistic integrity, they run the headline through
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  Speaker 1: an algorithmic optimization analyzer to score its click-through probability. We
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  Speaker 1: have arrived at a state of total epistemological paralysis, we
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  Speaker 1: no longer believe a human experience is real, valid, or
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  Speaker 1: valuable until it has been quantified, processed, and validated by
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  Speaker 1: an external software system. We have traded our internal human
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  Speaker 1: compass for a digital dashboard. Consider the hilarious architectural evolution
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  Speaker 1: of digital content creation in response to algorithmic incentives. In
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  Speaker 1: the early days of digital video platforms and online publishing,
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  Speaker 1: creators uploaded content based on personal passion, creative quirks, and
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  Speaker 1: unscripted human expression. A person filmed their hobby, shared a
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  Speaker 1: weird story, or wrote a quirky essay simply because they
• 12:18
  Speaker 1: felt a spontaneous urge to share something authentic with the world. Today,
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  Speaker 1: content creation has been entirely industrialized and dictated by algorithmic
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  Speaker 1: optimization guidelines. Creators spend hours analyzing back-end data analytics dashboards,
• 12:32
  Speaker 1: studying retention graphs, click-through rates, and algorithmic trend reports. They
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  Speaker 1: learn that to maximize algorithmic distribution, a video must open
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  Speaker 1: with a dramatic, high-energy 3-second visual hook. feature hyper-fast jump
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  Speaker 1: cuts every two seconds to prevent cognitive drop-off, utilize specific
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  Speaker 1: high-arousal background sound effects, and conclude with an urgent call
• 12:51
  Speaker 1: to action demanding that the viewer like, subscribe, and comment
• 12:54
  Speaker 1: below to trigger algorithmic engagement signals. The result is a
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  Speaker 1: wave of hyper-processed, identical, manic video content that looks and
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  Speaker 1: sounds as if it were manufactured by a single corporate factory.
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  Speaker 1: Creators no longer express their unique human voice, they perform
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  Speaker 1: as human puppets executing precise behavioral scripts dictated by the
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  Speaker 1: algorithmic preferences of a digital platform. They have surrendered their
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  Speaker 1: creative autonomy to become high efficiency distribution nodes for digital
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  Speaker 1: advertising space. Consider the profound psychological impact of algorithmic behavior
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  Speaker 1: modification on the human brain. Behavioral psychologists have long understood
• 13:31
  Speaker 1: the power of variable ratio reinforcement, the exact psychological mechanism
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  Speaker 1: that makes slot machines so violently addictive. If a lever
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  Speaker 1: yields a reward every single time it is pulled, the
• 13:41
  Speaker 1: brain quickly grows bored and stops pulling. But if the
• 13:44
  Speaker 1: lever yields a reward unpredictably, sometimes on the first pull,
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  Speaker 1: sometimes on the 50th, sometimes delivering a massive jackpot, sometimes
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  Speaker 1: delivering nothing, the brain enters a state of intense, hypervigilant compulsion.
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  Speaker 1: Modern algorithmic feeds are the ultimate variable ratio reinforcement engines
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  Speaker 1: ever constructed. Every time you swipe your thumb upward across
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  Speaker 1: a glass screen, you are pulling the lever of a
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  Speaker 1: digital slot machine. Nine times out of ten, the content
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  Speaker 1: delivered is mundane, boring, or uninteresting. But that tenth swipe
• 14:14
  Speaker 1: delivers a sudden hit of extreme hilarity, shocking outrage, deep
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  Speaker 1: visual beauty, or personal validation. Your brain releases a surge
• 14:22
  Speaker 1: of dopamine, locking you into a continuous, involuntary loop of swiping, searching,
• 14:26
  Speaker 1: and waiting for the next hit. We spend hours every
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  Speaker 1: day performing this mechanical biological ritual, flicking our thumbs across
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  Speaker 1: polished glass like lab mice pressing levers in a psychological experiment,
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  Speaker 1: completely oblivious to the fact that we are being systematically
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  Speaker 1: trained by mathematical models engineered to monetize our finite lifespan.
• 14:45
  Speaker 1: Consider how the algorithmic self has altered our relationship with spontaneous,
• 14:49
  Speaker 1: unscripted human discovery. Some of the most profound, transformative moments
• 14:54
  Speaker 1: in human history and personal life were born of pure,
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  Speaker 1: unscripted serendipity. You took a wrong turn down a city
• 15:00
  Speaker 1: street and stumbled upon a quiet bookstore that changed your
• 15:02
  Speaker 1: career path. You picked up an obscure, dusty record with
• 15:06
  Speaker 1: an interesting cover art and discovered a musical genre that
• 15:09
  Speaker 1: defined your youth. You sat next to a complete stranger
• 15:12
  Speaker 1: on a delayed train, struck up an awkward conversation, and
• 15:15
  Speaker 1: met your lifelong business partner or spouse. Serendipity requires friction, inefficiency,
• 15:21
  Speaker 1: wrong turns, and unstructured time. The modern algorithmic environment is
• 15:26
  Speaker 1: engineered to eliminate serendipity entirely. By anticipating your preferences, prefiltering
• 15:31
  Speaker 1: your choices, and guiding your movement through optimized digital and
• 15:34
  Speaker 1: physical corridors, the algorithm ensures that you rarely take a
• 15:37
  Speaker 1: wrong turn, rarely encounter an unfamiliar perspective, and rarely experience
• 15:41
  Speaker 1: a truly unexpected human event. We live inside a hypersanitized,
• 15:46
  Speaker 1: predictive bubble where everything is recommended, pre-approved, and tailor-made for
• 15:50
  Speaker 1: our existing profile. We have eliminated the risk of disappointment,
• 15:54
  Speaker 1: but in doing so, we have also eliminated the possibility
• 15:57
  Speaker 1: of wonder. Back in his dark bedroom, Nathan lay staring
• 16:01
  Speaker 1: at the ceiling. The $ 68 ergonomic lumbar cushion had been purchased,
• 16:05
  Speaker 1: the transaction confirmation email had arrived in his inbox, and
• 16:09
  Speaker 1: his smartphone screen had finally gone black on the nightstand.
• 16:12
  Speaker 1: The room was completely silent, save for the faint hum
• 16:15
  Speaker 1: of the air conditioner in the corner and the distant
• 16:17
  Speaker 1: sound of late-night traffic on the avenue below. Nathan turned
• 16:21
  Speaker 1: his head and looked at the dark glass rectangle resting
• 16:23
  Speaker 1: on the wooden table. He felt a sudden, strange impulse
• 16:26
  Speaker 1: rise from deep within his chest, a feeling of acute claustrophobia,
• 16:30
  Speaker 1: as if an invisible, lightweight net had been draped over
• 16:32
  Speaker 1: his mind, subtly guiding his thoughts, his purchases, his media,
• 16:36
  Speaker 1: and his daily choices for years without his explicit consent.
• 16:39
  Speaker 1: He sat up in bed, reached out, and picked up
• 16:42
  Speaker 1: the phone. He did not open his usual digital video apps,
• 16:45
  Speaker 1: social networks, or shopping platforms. Instead, he navigated deep into
• 16:50
  Speaker 1: the device settings menu, scrolled past the diagnostic metrics, and
• 16:54
  Speaker 1: located a small, buried toggle switch labeled, Reset Personalization Data
• 16:58
  Speaker 1: and Disable Predictive Recommendation Engine. He paused his thumb over
• 17:02
  Speaker 1: the toggle switch. A small warning box popped up on
• 17:05
  Speaker 1: the screen, reading, Warning, disabling personalized recommendations may result in
• 17:09
  Speaker 1: a less relevant, less efficient user experience. You will be
• 17:13
  Speaker 1: exposed to uncurated content that may not align with your
• 17:16
  Speaker 1: historical preferences. Nathan looked at the warning text. He read
• 17:21
  Speaker 1: the phrase less efficient user experience three times out of
• 17:24
  Speaker 1: loud in the darkroom. A soft, genuine laugh bubbled up
• 17:28
  Speaker 1: from his throat. He pressed his thumb down firmly on
• 17:31
  Speaker 1: the glass, toggling the switch to off. He closed the
• 17:34
  Speaker 1: settings menu, opened a digital music platform, and searched for
• 17:38
  Speaker 1: a completely random, unfamiliar keyword, traditional folk music of the
• 17:42
  Speaker 1: Outer Hebrides. He selected a obscure album recorded in 1962
• 17:46
  Speaker 1: featuring an unedited recording of an elderly Scottish fisherman singing
• 17:50
  Speaker 1: an unaccompanied Gaelic melody over the sound of breaking ocean waves.
• 17:54
  Speaker 1: He pressed play, set the phone face down on his chest,
• 17:56
  Speaker 1: and leaned back against his pillows. The music was raw, imperfect, strange,
• 18:01
  Speaker 1: and entirely unaligned with his historical digital data profile. The
• 18:06
  Speaker 1: acoustic quality was rough, the vocal scale was unfamiliar, and
• 18:09
  Speaker 1: the lyrics were sung in an ancient language he did
• 18:11
  Speaker 1: not understand a single word of. There were no algorithmic
• 18:15
  Speaker 1: jump cuts, no high-arousal sound effects, no optimized production hooks,
• 18:18
  Speaker 1: and no commercial sales pitches attached to the recording. It
• 18:22
  Speaker 1: was just the raw, uncurated, beautiful voice of a long-dead
• 18:25
  Speaker 1: human being singing across time into a dark suburban bedroom.
• 18:29
  Speaker 1: As the ancient Gaelic melody floated through the quiet room,
• 18:32
  Speaker 1: Nathan felt his central nervous system begin to unclench. The
• 18:36
  Speaker 1: ambient digital noise inside his skull began to dissipate. His
• 18:40
  Speaker 1: spine relaxed against the mattress without the aid of an
• 18:42
  Speaker 1: ergonomic lumbar cushion. His mind drifted away from predictive models,
• 18:47
  Speaker 1: engagement metrics, and optimized feeds, floating out into the vast, wild,
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  Speaker 1: unscripted ocean of real human history. He did not know
• 18:55
  Speaker 1: what the algorithm would serve him tomorrow. He did not
• 18:58
  Speaker 1: know what products he would buy, what news he would read,
• 19:01
  Speaker 1: or what path his career would take. He was completely
• 19:04
  Speaker 1: out of alignment with his data profile, unoptimized for digital
• 19:07
  Speaker 1: advertising networks, and thoroughly off the predictive grid. Nathan closed
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  Speaker 1: his eyes, took a long, deep, uncurated breath, and drifted
• 19:15
  Speaker 1: off into a deep, unmonitored, peaceful human sleep as 3,000
• 19:18
  Speaker 1: miles away, inside a silent, air-conditioned server farm, a mathematical
• 19:22
  Speaker 1: predictive algorithm logged an unexpected data anomaly, paused for a
• 19:25
  Speaker 1: fraction of a millisecond, recalibrated its parameters, and quietly waited
• 19:29
  Speaker 1: for the sun to rise.